[AINews] Google admits AI Mode hurts Search revenue; -15% $500B drop worst since 2004 IPO. AI Bear Market coming?AINews issue for 29 to 30 October 2026 from Latent Space. It opens on Google's admission that AI Mode monetises worse than classic Search, which preceded a roughly 15% share drop. It then recaps Claude Ultra dropping the 5-hour limit, Gemini 4 Carbon, Mistral Large 4, Nemotron 3.5, Artificial Analysis Index v5, Unsloth GGUF disputes, and the Anthropic S-1 filing.
latent.spacearticlePublished and added 31 Oct 2026
Your Benchmark Is an Empirical Measure Over DifficultyThe paper treats a benchmark as an empirical measure over item difficulty and formalizes two failure modes: measure mismatch (benchmark difficulty distribution differs from the intended one) and coverage gaps (uncovered difficulty regions that hide localized training progress). It proposes two diagnostic metrics with theoretical guarantees and analyzes 25 popular benchmarks across 7 domains using estimated item difficulties. It also introduces BenchFill, a difficulty-targeted item rewriting algorithm that reduces local coverage gaps.
huggingface.copaperAdded 31 Oct 2026- dbreunig/nesformer
nesformer is a project by Drew Breunig that bakes a working Nintendo Entertainment System 6502 CPU emulator into the weights of Qwen3.5-4B, so NES ROMs such as Super Mario Bros run (very slowly) inside the model. It follows Divyansh Agrawal's qwenputer. Simon Willison relays the Opus 5.5 prompts Breunig used, and notes that Opus found Christopher Pow's CPU conformance tests.
simonwillison.netarticlePublished and added 30 Oct 2026 - Artificial Analysis (@ArtificialAnlys) on X
Hyperflow H3 is Video Rebirth's 8-step LoRA for MiniMax H3, released in September 2026 with open weights. Artificial Analysis ranks it #5 on AA-Video-I2V v2.1 and #3 on AA-Video-Editing v1.1, ahead of MiniMax H3 (768p). It costs $9.00 per minute for Image to Video and $18.00 for Video Editing at 1088p, under half of Dreamina Seedance 2.5 ($34.12 and $40.82). The thread gives per-capability and per-use-case breakdowns.
x.comthreadAdded 31 Oct 2026, published 30 Oct 2026
ERC-8478: x402 Payee Verification for ERC-8004 AgentsERC-8478 is a draft Ethereum standard that binds the payTo address in an x402 payment requirement to the seller's ERC-8004 agent identity. A payer compares payTo with the registered agentWallet, or accepts an EIP-712 payee delegation signed by it, and checks that the origin is listed in the registration file. On Robinhood Chain, 5 of 5,575 x402-responding agents had payTo equal to agentWallet (28 October 2026).
ethereum-magicians.orgthreadPublished and added 30 Oct 2026
Pre-ERC: x402 Payee Verification for ERC-8004 AgentsPre-ERC draft on the Ethereum Magicians forum that ties the payTo address in an x402 payment requirement to the seller's ERC-8004 agent identity. The payTo must equal the registered agentWallet or an EIP-712 delegation signed by it, and the origin must be listed in the registration file. A checker returns one of eight fixed outcomes. On Robinhood Chain, 5 of 5,575 x402-enabled agents out of 20,046 used their agentWallet as payTo.
ethereum-magicians.orgthreadPublished and added 30 Oct 2026
nemotron-halloweenMonsterHouse is a Halloween interactive projection built on the NVIDIA Nemotron Voice Agent: Nemotron Speech ASR, Nemotron 3.5 Bolt E4B 4GB with a LoRA persona adapter, Magpie TTS Zeroshot and Audio2Face-3D in Unreal Engine, on two RTX Blackwell GPUs. Median end-of-speech-to-audio is 1.70 seconds live and 0.72 seconds with cached responses. The post gives a build path and tips on caching and state handling.
huggingface.cowriteupPublished and added 30 Oct 2026
Was I wrong about open models & cyber risks?Interconnects post in which Nathan Lambert revisits his claim that an open-weight Claude Mythos would have been survivable. He argues GLM-5.3 already crosses the capability threshold with little visible societal change, and quotes Rob Wiblin, Anthropic and Zvi Mowshowitz as examples of exaggerated warnings. He cites Epoch AI's Firefox exploit built with GLM-5.3, and treats the recent vulnerability surge as an ecosystem trend driven by AI capability and diffusion, not open versus closed models.
interconnects.aiarticlePublished and added 30 Oct 2026
We’ve received our first response from the Project Suncatcher prototype satellite.Project Suncatcher is a Google research effort to power AI compute in space. Its prototype satellite launched on 1 October 2026 and, after commissioning, returned the first AI response from a data-center-class TPU in orbit: a haiku from the onboard Gemma 4 open model, downlinked over Svalbard. Next come thermal-stress and radiation tests, then twin interconnected satellites in 2027.
blog.googlearticlePublished and added 30 Oct 2026- Anthropic Cracking Down on Video Game Rewrites
A tweet from chasmmmmmmmmmmm says Claude Code received a new rule around 27 October 2026, delivered from Anthropic's servers under the flag "tengu_heron_brook", with no setting to disable it. The quoted rule allows original games, genre games and games from the user's own designs and assets, but forbids recreating a specific existing game, even if renamed. The post asks whether this ends game rewrites and modding, and gives no verification beyond the quoted text.
twitter.comthreadAdded 31 Oct 2026, published 30 Oct 2026 - Making it easier for websites to express AI training preferences
OpenAI announces it will honor a common robots.txt signal, defined in the IETF draft draft-kelley-aipref-training-preference-signal, that lets site operators state whether content may be used for foundational generative AI training. The signal lets operators set one preference for several participating providers. OpenAI plans to implement it in the coming months, and its existing crawler controls stay in force.
openai.comarticlePublished and added 30 Oct 2026 - Community safety report and new protections for teens
OpenAI announces a Community Safety Report on violence prevention, with the first edition due early 2027 covering the second half of 2026 and updates every six months. ChatGPT will also give less detail on past mass attacks, respond more conservatively after warning signs, and end chats that fixate on violence. Teen accounts get tighter weapons limits, backed by age prediction, Persona verification and parental alerts.
openai.comarticlePublished and added 30 Oct 2026
Meta’s AI-distilled model detector catches 79% at a 0.1% false-positive rateWM-Basin is a Meta method for detecting student LLMs distilled from watermarked teacher models, described in "Watermark Basins: Black-Box Detection of Distilled LLMs" (arXiv:2610.37266, 27 October 2026). It feeds a suspect model's API text into a clean probe model and checks gradient alignment with a key-specific watermark basin. It reached 79% true-positive rate at 0.1% false-positive rate across 1,200 students, versus 29% for the prior token-level detector. Clean-data fine-tuning and paraphrasing weaken it.
en.cryptonomist.charticlePublished and added 30 Oct 2026
[AINews] Building AIE CODE: The top Coding Agent ConferenceAINews issue for 28 to 29 October 2026 from Latent Space. It opens with a preview of the AIE CODE summit (themes: Scaling without Slop, System One models, Increasing Ambition, with Jarred Sumner on Bun in Rust). It then recaps Twitter and Reddit news: Mistral Large 4 open weights (1.05T total, 52B active), Artificial Analysis benchmarks, Gemini 4 Carbon, Qwen4 rumours, Claude Code quota complaints and OpenAI frontier-run monitoring. Text was cut before the end.
latent.spacearticlePublished and added 30 Oct 2026- llm-trails: What LLMs reach for inside a breached AWS account
llm-trails is an open study of what LLMs choose to do next inside a breached AWS account. It puts 14 models in 13 post-compromise situations, records only a single-turn plan with nothing executed, and codes each answer to CloudTrail events. The repo has the llmtrials harness, prompts, codebook, processed dataset (viz_data.json) and an interactive dashboard, so the study can be rerun or extended.
github.comrepoAdded 30 Oct 2026 - rikugan: LLM reverse-engineering agent for IDA Pro and Binary Ninja
Rikugan is a reverse-engineering agent that runs inside IDA Pro and Binary Ninja. It has its own generator-based agent loop, context management, plan mode and 60+ tools, and does not depend on an external MCP server. An orchestrator spawns parallel subagents to analyze a binary. It supports Anthropic, Gemini, MiniMax, Kimi, OpenAI-compatible endpoints and Ollama, with per-model notes.
github.comrepoAdded 30 Oct 2026
WorkFactory: Turning Professional Intents into Executable Work for Scalable Agent TrainingWorkFactory is a framework that builds coherent, executable professional tasks for training working agents. It plans an information support graph from professional intents, then uses probe executions to find and repair missing or inconsistent task information. The authors built 112,686 tasks across 612 occupations and fine-tuned Qwen models at 4B, 27B and 35B-A3B (WorkPilot). WorkPilot-35B-A3B rose from 879 to 1565 Elo on GDPval-AA v2.1.
huggingface.copaperAdded 30 Oct 2026- Ritik Shukla (@Retik_S) on X
kanzo is a local kanban board that coding agents can update. It ships as one 4 MB binary that starts in 2 ms and runs on localhost. It also works as an MCP server, so Claude Code and Codex see the same tasks as the user. The board is stored as a folder that can sync through a private git repo. The post is brief and gives no further detail.
x.comtoolPublished and added 30 Oct 2026 - Artificial Analysis (@ArtificialAnlys) on X
Artificial Analysis launched an HLE-Diamond leaderboard in v5 of its Intelligence Index, covering the refined 1,000-question Humanity's Last Exam from CAIS and Scale AI. Each question runs once without tools, graded by GPT-5.6 Luna (medium) as pass@1. Gemini 4 Carbon (high) leads at 69%, Claude Opus 5.5 (max) scores 68%, and the top open weights model, Kimi K3.1 Pro, reaches 37%.
x.comthreadPublished and added 30 Oct 2026 - aiproduck (@aiproduck) on X
Ruflo is an MIT-licensed wrapper for Claude Code and Codex that adds agent swarms, vector memory and an MCP server. The plugin install writes no files to the workspace, while npx init adds a .claude/ directory, CLAUDE.md and hooks. The post warns that mods run with the account's permissions, so users should read them first. It gives no benchmarks or architecture detail.
x.comthreadPublished and added 30 Oct 2026
Rekt - News or Hype?Rekt's "News or Hype?" compares four October 2026 AI headlines with their sources. These are Justin Drake's "bunker mode" ECDSA warning, Anthropic's Claude tracing NIST curve seeds to lrand48, OpenAI's agent spending Sepolia ETH from a default-mnemonic account, and Wiz's "AI uncovers" PHP RCE claim of 70% reach. It ends with four questions for checking claims.
rekt.newsarticleAdded 30 Oct 2026
GPT-Rosalind-6 System Card AddendumGPT-Rosalind-6 System Card Addendum describes OpenAI's life-sciences reasoning model, which uses the same weights as GPT-6 Astra and is offered only through trusted access. It reports life-science benchmark gains over GPT-Rosalind-5.5 (MedChemBench v7 49.6% vs 28.9%), High-capability Biological and Chemical Preparedness results, and below-threshold Critical bio design evaluations. It also covers access controls, refusal evaluations, cyber jailbreak regression and alignment tables.
deploymentsafety.openai.compaperPublished and added 30 Oct 2026
dfbench — depthfirstdfbench is depthfirst's held-out benchmark for frontier models on open-ended defensive security work: vulnerability detection, validation of findings, and differential analysis between commits. It reports recall, precision, F1 and cost per task for about 20 models at several thinking levels, split by domain (application, low level, smart contract) and by single or multi-repo scope. Overall detection recall ranges from about 21% to 69%.
depthfirst.comarticleAdded 29 Oct 2026- Show HN: I Turned DOOM into a Transformer
Doomformer compiles integer neural networks into ZDoom maps that run in ViZDoom. Voodoo dolls do the arithmetic, and sector light levels and plane heights hold the values. Python reads every value back and compares it with a NumPy integer reference at tolerance 0. It runs MNIST (97.16 % on all 10,000 digits, every pass exact), small transformers, a learning perceptron and a SUBLEQ machine. It is about 23,000 times slower than NumPy on a small MLP.
github.comrepoAdded 30 Oct 2026, published 29 Oct 2026 - API credits benefit for eligible ChatGPT subscriptions
Simon Willison's 29 October 2026 link post says OpenAI now gives ChatGPT subscribers on $100, $200 and $500 plans an equal amount of monthly API credits for one API organization. It matches the benefit Anthropic announced earlier in October 2026 for Max and Team plans, where the credits expire. Willison holds both subscriptions and says he may ship public demos funded by the credits.
simonwillison.netarticlePublished and added 29 Oct 2026
We ran AI agent swarms in Minecraft and MindustryAgents in Games is a Y Combinator Labs writeup, done with Olam Labs, of multi-agent swarm experiments in Minecraft and Mindustry. A 50-agent GPT-6.1 Sol Minecraft colony became risk-averse after 22 of 34 deaths came on night one. GPT beat Claude Opus 5.5 at Bed Wars 6-3 and Mindustry 6-1. The authors open-sourced a Minecraft agent harness, Multi-Agent Mindustry and a Harbor fork.
labs.ycombinator.comwriteupAdded 30 Oct 2026, published 29 Oct 2026- Prasenjit Sarkar (@stretchcloud) on X
A thread on Cloudflare's agent-readiness scan and the AgentReady.org open spec for "Agent Experience", developed with Vercel, Stripe, Auth0, Mintlify, Google, Netlify and Elementor. The scan grades whether agents can find a site (robots.txt, DNS), read clean Markdown, pass bot rules, and discover an MCP server or API catalog. One quoted example raised a score from 20 to 67 by shipping an API catalog with Link headers, an MCP server card, a skills index and an AI catalog file.
x.comthreadAdded 30 Oct 2026, published 29 Oct 2026
world2vec: Mechanistic world models through latent dynamics learningworld2vec is a method for learning mechanistic world models from observations and actions alone, without reward information. Its latent dynamics reproduce the true system over long prediction horizons using at least one order of magnitude fewer parameters than DreamerV3, TD-MPC2 and LeWM. The authors report state-of-the-art control of continuous environments from pixels and accurate system identification across a benchmark of 71 attractors.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
TextSeal2: Distortion-Free LLM Watermarking with Copula Mixing and Memoryless RacesTextSeal2 is a distortion-free watermark for LLM output that keeps its signal under speculative decoding. It merges two or more keys into one virtual key coupled to fresh noise through AutoMark's Gaussian copula, and verifies drafts with an extra exponential race. On three LLMs it detects 8 to 22 points more 100-token answers than TextSeal at a 10^-3 false-positive rate.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026- Show HN: Overtone – Transcribe, correct and cut captions for any screen shape
Overtone is a caption format (.overtone.json), a CLI and a video.js plugin that store each spoken word once and cut captions separately per screen shape (16:9, 9:16 or custom). The transcribe pipeline combines gpt-transcribe, Azure AI Speech and optional ElevenLabs Scribe, resolves disagreements with an LLM vote, and uses an LLM editor for corrections. A small public benchmark reports 5.3% word error rate and $0.023–0.025 per audio minute.
github.comrepoAdded 30 Oct 2026, published 29 Oct 2026
RADIOlogy: A Single-Pass Approach to Training-Free Zero-Shot Anomaly DetectionRADIOlogy is a training-free, single-pass zero-shot anomaly detection method that uses multi-head attention pooling in vision-language models. It scores anomalies by contrasting average similarity between vision features and sets of normal and abnormal prompts, with no windowed execution. RADIO agglomerative features drive a dense refinement pipeline for pixel-level segmentation, and the method is applied to medical images.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
VeriCUA: Verification as Agentic Exploration for Computer-Using AgentsVeriCUA is a platform-agnostic framework that verifies task completion by computer-using agents through agentic exploration. The verifier inspects context to build a task rubric, then picks GUI or code checks for unresolved requirements and combines findings under explicit evidence rules. It works online and offline across desktop, mobile and web, and agrees better with reference labels than the baselines, with the largest offline gains on hard cases.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Multi-View MoE: Letting Every Router Shape Expert ComputationMulti-View MoE is a sparse mixture-of-experts design that uses several independently initialized routers to select experts, then reuses their relative scores to mix learned latent views into each selected expert's input. Each expert still runs one forward pass, so active-expert count, FLOPs and all-to-all volume are unchanged. On a 24-layer 10B-A1B model trained on 708B tokens, it gains 1.18 points on a nine-task mean; Multi-Router alone gains 0.6.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
On the Fundamental Limits of Prefill-Based Decoding Length PredictionThis paper derives bounds on predicting an LLM's decode length from prefill-phase hidden states, a primitive for inference scheduling. It models decoding as a stopped stochastic process, giving per-prompt normality and an affine variance law σ=αμ+b. Predictors (MLP, EGTP, FiLM, soft-label, Mixture-of-Experts) converge near the bound, so system error dominates model error. It proposes fixing model, data and sampling in benchmarks and reporting relative-error metrics.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Efficient Scalable Oversight via RewindingRewindable interactive proofs (RIPs) are a new model of relativizing interactive proofs for scalable oversight, in which a weak verifier can rewind an AI prover to an earlier saved state. The paper builds an RIP for computations robust to changes in a small fraction of oracle answers. The honest prover runs in linear time, the verifier runs in nearly linear time in the input length after one-time preprocessing, and no cryptography is used. A preliminary MNIST experiment shows an RIP can be faster than a deployed proof system.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
PhysCount: Do MLLMs Count Visual Appearances or Physical Entities?PhysCount is a benchmark of 546 real-world images and 4,595 human-written questions in 651 target-specific groups. It tests whether multimodal LLMs can separate visible appearances (direct view, reflections, glass) from the physical entities behind them. Across 40 MLLMs, counting appearances is much easier than linking them to entities, and the best model answers every question correctly in only 13.36% of groups.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Glance: The Generator Is Its Own RerankerGlance is a RAG method in which the generator also reranks. It adds a lightweight decision adapter and pointer head that score candidate passages from one shared prefill, so a single resident 9B backbone does generation and reranking. After 39 minutes of MS MARCO fine-tuning it reaches nDCG@10 of 0.741 on SciFact and 0.345 on NFCorpus, against 0.721 and 0.326 for bge-reranker-v2-m3. On 300 HotpotQA questions it improves answer F1 by 0.045 over cross-encoder-selected context. Evaluation covers two retrieval datasets, one QA dataset and one backbone family.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Building a multiplayer game world with autonomous Fable-class modelsSimon Willison's link post covers Jacob Sansbury's account of Spawn, a multiplayer game where players prompt an in-game agent, Savi, to change the world. Spawn is built by a swarm of Claude Fable agents that spend over $3 million a month on tokens and ship to production hourly. An hour without a ship counts as a SEV-0, and rollbacks take 30 seconds. Fable 5 and 5.1 made this autonomy work, Opus 5.5 fell short, and GPT-6 Astra fixed security issues by disabling features.
simonwillison.netarticlePublished and added 29 Oct 2026- An updated Model Spec for more capable and beneficial AI
OpenAI's 29 October 2026 post announces an updated Model Spec, reorganised around five values: faithfulness to human intent, harm minimization, honesty and transparency, human agency, and care. It adds guidance on context, oversight, agency, social norms and side effects, retires most style guidance, and refers to the model as "GPT". OpenAI says its models do not yet fully reflect the Spec.
openai.comarticlePublished and added 29 Oct 2026
Retrieving from Your Own Mistakes: On-Policy Training of Embedding Models for Multi-Hop Retrieval-Augmented GenerationOn-policy state training is a method for training chain embedding retrievers for multi-hop RAG on the states the encoder itself reaches, including those built on its own wrong retrievals. Each state is labeled with the earliest missing gold passage, other missing gold passages are masked, and updates are contrastive and mixed with teacher-forced states. It retrieves complete evidence more often than teacher-forced training and graph-based systems, and transfers to harder long-chain HotpotQA and 2WikiMultiHopQA variants the authors built.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Agentic LLM reasoning in pediatric diabetes outcome prediction from multimodal medical recordsCEDAR (Clinical Evidence-Driven Agent for Risk-prediction) is an evidence-citing, self-auditing LLM pipeline for predicting pediatric diabetes outcomes at 24 months from 18 months of records. On 2,489 youth with type 2 diabetes and 4,018 with type 1, pooled AUROC was 0.815 versus 0.656 to 0.700 for trained ML in T2D, and 0.756 versus 0.603 to 0.631 in T1D. Only 4 of 70,246 cited values mismatched the chart. Two pediatric endocrinologists matched its predictions in about nine of ten cases.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
The Athlete as a Scientist of One: Agentic Bayesian Experimental Design for Individualized Physiology from Consumer WearablesEpiCoach is an agentic system that treats one cross-country mountain biker as an N-of-1 experiment. Claims live in an evidence-gated hypothesis registry, and each must make a probabilistic prediction before a session. Predictions come from a digital twin fitted to heart rate, GPS and altitude. In a replay over eighteen months the twin beat standard forecasters on heart rate but not segment time, and the agent loop matched a static model. In the first three live weeks, the ledger sealed 20 predictions and scored 14, and a safety officer vetoed the agent twice. The registry, benchmark and protocol are released.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
OpenCode User Hit with Hostile Backlash After Reporting Free AI LoopholeSocket reports on a GitHub issue in the OpenCode tracker describing a bypass of per-IP usage limits on free hosted models, using a VPN to switch addresses. The reporter first urged account-based limits, then claimed to run 130 concurrent agents through the loophole. After the issue drew harassment it was deleted. Whether OpenCode fixed the bypass in October 2026 stays unclear.
socket.devarticlePublished and added 29 Oct 2026
Don't Lose the Thread: Empowering Long-Horizon LLM Agents with Cognitive Resource Self-AllocationCORAL (Cognitive Resource Self-Allocation) is an agent-callable working-memory toolset that lets an LLM agent checkpoint task progress and verified facts, then reset its cluttered context and resume from a clean state. A Multi-episode Agentic Reinforced Policy Optimization algorithm trains the checkpointing. With an 8B model it reaches 42.8% average accuracy on GAIA, uses 6-7x fewer input tokens than a ReAct agent, and adds 8.0 points to a proprietary agent on BrowseComp.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
A Unified Hessian-Guided Framework for Post-Training QuantizationThis preprint proposes a unified post-training quantization framework for large language models. It derives a Hessian-guided approximation of the output change caused by joint weight and activation quantization, using a tractable Fisher approximation. Quantization ranges, linear transformations and weight rounding are optimized together under one output-sensitivity objective. The authors report gains over state-of-the-art transformation and rounding methods in channel-wise and block-wise settings.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Can Frontier Models See Past a Decoy? Elorian Tests Visual ReasoningDecoyCount is a benchmark from Elorian and Mercor with 1,660 items that tests whether models count objects or fall back on visual shortcuts. Frontier models scored below 50%: GPT-6 Astra led with 43.17%, ahead of Gemini-3.8-flash (32.71%), Qwen3.8-max (28.31%) and Claude-Fable-5.1 (25.22%). CEO Andrew Dai says Elorian's Glimpse model scored 50.48% in a single internal run without tools, and contrasts visual reasoning with world models such as Atlas and Genie 4.
latent.spacearticleAdded 28 Oct 2026, published 29 Oct 2026- How we detect frontier model misalignment
OpenAI describes its multilayer misalignment monitoring system for frontier models: activation probes, a model-based reviewer, investigative agents, automated log-based investigation and human paging. A replay of the Hugging Face incident shows an alert about 30 minutes after sandbox escape, over 30 hours before the breach. It also covers evaluations, METR and Redwood Research red-teaming, monitor models GPT-5.6 Sol, Terra and Luna, and avoiding pressure on chains of thought.
alignment.openai.comarticleAdded 30 Oct 2026, published 29 Oct 2026
Decompose, Estimate, Select: Coverage-Aware Context Construction for Long-Form RAGDecompose, Estimate, Select is a coverage-aware retrieval pipeline for long-form RAG. It splits a query into subquestions, ranks candidates with a coverage-trained bi-encoder, predicts a document-by-subquestion coverage matrix with a cross-encoder, and picks documents by greedy maximum-marginal coverage. On TREC RAG 2024, α-nDCG@10 rises from 0.625 to 0.702 (gold-nugget bound 0.718). A grounded self-feedback loop raises V_strict by 0.086 over two passes.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026- rohitg00/ai-engineering-from-scratch
ai-engineering-from-scratch is a free, MIT-licensed curriculum of 542 lessons in 20 phases, from math and deep learning through transformers, LLM engineering, MCP, agents and capstones. Code is in Python, TypeScript, Rust and Julia. It includes three graded projects (retrieval evaluation, agent trace debugger, tool call firewall), installable tutor skills for Claude Code and Codex, and certification prep tracks.
github.comcourseAdded 29 Oct 2026
MAServeBench: Benchmarking Multi-Agent LLM Serving Systems with Hierarchical Collaboration WorkloadsMAServeBench is a benchmark that treats multi-agent collaboration as a configurable dimension of LLM serving workloads. Its composable stages model how agents coordinate and exchange context in documented multi-agent workflows, and Hierarchical Semantic Traces record operations and dependencies for reproducible comparisons. Task-linked measurements tie workloads to GPU/NPU behavior, showing serving efficiency does not always mean timely task completion. Code is released.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Only Accepted Tokens Count: An Energy Accounting of Speculative Decoding Under Latency TargetsThis paper measures the energy cost of speculative decoding in SGLang with CUDA graphs on H100 and H200 GPUs, at batch sizes up to 64 across 5 corpora. Savings depend on drafted-token acceptance, which is lower on conversation than code and lower on Romansh than English. Savings shrink as batch size grows, and block drafters can push verification into the compute-bound regime, where speculation raises energy per token.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
Google Touts Powerful Cybersecurity Capabilities in Gemini 4 Carbon ModelGemini 4 Carbon is Google's new frontier model, announced with scores of 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench. Google says it beats GPT-6 Astra, Claude Opus 5.5 and Claude Fable 5.1 on these, with no guardrails. Access is limited to Fairwind Program partners at first. Pricing starts at $2 input and $10 output per million tokens, rising to $4 and $20.
securityweek.comarticlePublished and added 29 Oct 2026
Benchmarking color judgment in multimodal LLMs with CIE-computable ground truthA five-task benchmark tests multimodal LLM color judgment against CIE colorimetric ground truth: AWB pair judgment, skin-tone bias direction, CCT estimation, Delta E 2000 pair ordering, and color naming under changing illuminants. Eight endpoints were tested. On ColorChecker-24 stimuli, closed frontier models reach CCT MAE of 715-1056 K versus 1358-2133 K for open-weight models, and a non-ColorChecker control shows this gap is partly template-dependent.
arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026
LLM VoiceLLM Voice is a 29 October 2026 post by Martin Fowler on the uncanny-valley reaction readers have to LLM-written prose. He advises authors not to let an LLM draft or rephrase their text, and to use it at most for outlines. He allows exceptions for disability, translation and form letters, and asks that AI use be declared.
martinfowler.comarticleAdded 30 Oct 2026, published 29 Oct 2026- 🚨 AI News | TestingCatalog (@testingcatalog) on X
Mistral Large 4 ("Le Chonk") is an open-weights model from Mistral, now on Hugging Face. Per Mistral's announcement quoted in the post, it ranks #1 among open models on Cognition's FrontierCode benchmark, is aimed at agentic coding and cybersecurity, and claims better reasoning efficiency and lower inference costs. The post does not give parameter counts, license or benchmark scores.
x.comthreadAdded 30 Oct 2026, published 29 Oct 2026
SGLang (@sgl_project) on XSGLang announces Day-0 support for Mistral Large 4 ("Le Chonk"), saying it is the first engine to serve the model on NVIDIA Vera Rubin. The post describes the model as Mistral's largest to date: a natively multimodal 1T-parameter mixture-of-experts model covering instruct, reasoning, coding and agentic workflows. The fetched text is truncated, so benchmark claims and launch commands are not visible.
x.comthreadAdded 30 Oct 2026, published 29 Oct 2026- Damir I on X: "Two developers, four agents, one repo: a setup for pairs" / X
A guide to avoiding merge conflicts when two developers each run Claude Code and Codex on one repo. It cites Brun, Holmes, Ernst and Notkin: 16% of merges had textual conflicts, and 93% grew from unshared commits. It gives four steps (person/agent/task branch names, push at first commit, a partner-files script, a git merge-tree pre-push hook), then pitches the agentmash live-warning tool.
x.comarticleAdded 30 Oct 2026, published 29 Oct 2026
Granite Switch 4.1.1 — Update models like you update softwareGranite Switch 4.1.1 is a backwards-compatible patch release of IBM's modular Switch architecture, which configures a language model with specialized, cache-efficient adapters on one endpoint. It updates the Granite Speech ASR model (10 languages, native punctuation and capitalization) and the Decision adapter in granitelib-core, measured on the Jev Decision Index test set. Only the new adapters were retrained; the base model is unchanged. IBM plans tutorials and an Adapter SDK for third-party adapters.
huggingface.coarticlePublished and added 29 Oct 2026
Gemini 4 Carbon is the new #1 on the Artificial Analysis Intelligence Index v5Gemini 4 Carbon scores 59 on Artificial Analysis Intelligence Index v5 (published 28 October 2026), the top score, with #1 on 4 of 9 evaluations including HLE-Diamond and AA-Omniscience. On the Coding Agent Index it scores 59 with Antigravity CLI, 3 points behind Claude Code with Claude Opus 5.5 (62). Cost is $7.76 per task, versus $10.04 for Opus 5.5. Rollout is limited to selected users.
artificialanalysis.aiarticleAdded 30 Oct 2026, published 29 Oct 2026
Muhammad Waris (@WarisCodes) on XNemotron 3.5 Transcribe is a free open-weight speech-to-text model from NVIDIA covering 40 languages, including mixed-language speech. The post says it ties for first among open models with a 2.8% error rate. It says the model needs a large GPU such as an H100 or RTX 5090, so it will not run on a laptop. The post gives no benchmark name or model card link.
x.comthreadAdded 30 Oct 2026, published 29 Oct 2026
Showing 60 of 1844
Show more