249 results for “TIME”

Speculative naming is a fine-tuning-free method that cuts character-name repetition in LLM fiction. It adapts draft-verify-reject from speculative decoding to names, using verbalized sampling and a SlopTracker that combines a per-model fingerprint with a runtime counter. Across 20 LLMs and 44,782 stories in four languages, it cut Slop Ratio by 95% and mean collision probability from 7.3% to 0.4%. Static banlists only displaced the concentration to emergent names.

arxiv.orgpaperAdded 3 Nov 2026, published 31 Oct 2026🧠 AI

AgentCap is a runtime authorization layer for LLM agents that moves the authorize decision out of the model and mediates every tool call through an MCP wrapper. It issues short-lived, budget-bounded capability tokens checked at the tool boundary, restricts delegation to attenuating parent-child chains, and uses a declarative policy language. On AgentDojo and InjecAgent it lowers attack success in every tested setting, reaching 0% with GPT-5.4.

arxiv.orgpaperAdded 3 Nov 2026, published 31 Oct 2026🛡️ Security

AgentCap is a runtime authorization layer for LLM agents from Virginia Tech (Suresh and Gao), posted to arXiv on 31 October 2026. The model proposes MCP tool calls, and a policy engine issues Ed25519-signed capability tokens only after checks on provenance, intent, trust and prerequisites. It reports 0% attack success with GPT-5.4 on AgentDojo and InjecAgent, but only on scenarios the authors built.

arxiv.orgpaperAdded 3 Nov 2026, published 31 Oct 2026🧠 AI

Economic-State Manipulation (ESM) in DeFi is studied using 276 real-world attacks and 91 Code4rena audit findings. The authors build a cause-based taxonomy of four categories and eleven subcategories, showing these flaws go beyond price manipulation to accounting, AMM state consistency and execution-time violations. Seven detection approaches were evaluated; the best found only 50.4% of real attacks.

arxiv.orgpaperAdded 3 Nov 2026, published 31 Oct 2026🛡️ Security

This paper introduces a grammar-lens benchmark, derived from the theory of computation, that generates novel data at levels of increasing computational power. GPT-5.5 and GPT-5.5-Pro at Medium, High and XHigh reasoning accepted 16, 40, 43 and 52% of test data. As test-time effort rose, model answers diverged more from human answers on the same data. The authors suggest this may reflect a general capability-versus-alignment conflict.

arxiv.orgpaperAdded 3 Nov 2026, published 31 Oct 2026🧠 AI

LOCOGEN is a sampling-time guidance method for diffusion models that design regulatory DNA sequences. It learns an invariant motif mask through sequence-level invariance learning, protects motif positions, and applies out-of-distribution damping only to background positions, with no retraining of the frozen backbone. On HepG2, K562 and SK-N-SH it reaches a region of the property, novelty and plausibility space that no baseline reached. Code is released.

arxiv.orgpaperAdded 3 Nov 2026, published 30 Oct 2026🧠 AI

Rewindable 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🧠 AI

EpiCoach 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🧠 AI

MAServeBench 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🧠 AI

Kolesnikov and Novoselov give block basis reduction (BKZ) algorithms for linear codes that need polynomial or quasi-polynomial numbers of calls to a minimum weight codeword oracle at fixed block size. The earlier Ghentiyala and Stephens-Davidowitz bounds are exponential. The paper adds a truncated BKZ and a DeepBKZ variant, with an implementation for block sizes 2 to 24 and approximation-factor estimates on random codes.

eprint.iacr.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🛡️ Security

AutoBench-CT is a modular benchmark for constant-time analysis tools, with manually verified per-violation ground truth across 64 cryptographic tasks. It scores seven tools on operational performance, detection quality and usability. The authors explain why CT-grind (2010) is still the most used tool, list recurring limitations across tools, and propose a composite pipeline for stronger constant-time guarantees. Accepted at ACSAC 2026.

eprint.iacr.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🛡️ Security

Turing LLM post-training combines calibrated multi-teacher on-policy distillation (C-MOPD) with an execution path for dynamically routed mixture-of-experts models. C-MOPD matches each teacher on a local Top-K support with teacher-wise loss normalization and clipping. On Turing-20B-A2B it scores 0.9988 on four-domain integration, beats Qwen3-8B on math and code (85.92 vs 80.33 mean), and cuts consolidation step time from 398.7 to 139.3 seconds in a PPU profile.

arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🧠 AI

Cryptanalysis of VTBSAE, a verifier-based PAKE protocol for the Industrial Internet of Things, showing it fails to resist client impersonation after server compromise. The authors propose E-VTBSAEv1, which binds the client point E1 to fresh server randomness, and prove AKE security and forward secrecy in the random-oracle model under CDH. Raspberry Pi 4B tests show runtime comparable to VTBSAE with the same communication and storage overhead.

eprint.iacr.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🛡️ Security

REALM (Required Execution Assets Linked to a Mission) is an approach to applying least privilege to LLM agents by identifying the assets a task needs, including ones discovered at runtime. It models assets as Dependency Graph nodes, separates discovering an asset from authorizing it, and exposes resource-bound Partial APIs inside a Task Container. On AgentDyn with qwen3.5-flash, attack success rate falls from 16.6% to 0.2%, with 40.0% task completion on clean tasks and 36.4% on injected cases.

arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🛡️ Security

DeoGen is an automatic, parametrizable benchmark generator for deontic reasoning, where a model applies policy rules to facts to reach a verdict. It autoformalizes rules into first-order logic, builds decision trees, and turns each tree path into a benchmark entry. Frontier models give the correct verdict 89-92% of the time, but only 22-40% on entries lacking enough information, even when told to abstain.

arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

AskStream is a multi-turn benchmark for streaming video understanding that adds a third proactive action, ask, alongside wait and answer, for cases where video or user information is incomplete. It has 438 videos, 2,714 manually annotated frame-level time windows (wait, ask, answer), four task categories and eight subtasks. The strongest model reaches only 52.18% on the proposed Ask-F1 metric, in both multiple-choice and open-ended settings.

arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

Shor's algorithm compiled on cat qubits is an IACR ePrint (2026/2665) giving an end-to-end resource estimate on superconducting cat qubits, using repetition and LDPC cat codes. Factoring RSA-2048 needs about 23,000 cat qubits and 3.14 days, assuming phase-flip noise p_Z = 5e-4 and no bit-flips. secp256k1 ECDLP needs at most 30,000 qubits and 1 hour. A space-for-time trade runs RSA-2048 in 1.25 hours on about 611,000 qubits.

eprint.iacr.orgpaperPublished and added 28 Oct 2026🛡️ Security

JevAct is a runtime verification framework that intercepts selected LLM agent actions before execution and returns feedback for bounded revision. It compiles domain policies into executable state checks and structured questions scored by a prefill-only decision model, giving probability-based judgments without generation. Tested on eleven agents with tau^2-bench Airline and Telecom and BFCL, it gained consistently on Telecom and BFCL and was mixed on Airline.

arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

CALM is a conflict-aware lifecycle memory governance framework for long-horizon language agents. It turns records into evidence-grounded memory cells, updates their validity and lifecycle states from support, conflict and dependency signals, and admits evidence at query time through training-free or learned gating based on temporal applicability. It beats baselines on LongMemEval-S and LoCoMo with Qwen and GPT backbones, and keeping superseded records helps earlier-state reasoning.

arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

VulnLens is a framework for binary C/C++ function-level vulnerability detection. A label-blind LLM Explainer describes each function from seven fixed perspectives (data flow, memory access, object lifetime, arithmetic and type behavior, control flow, shared state, external-resource access). A supervised Detector fuses code and explanations by cross-attention. It reaches 75.5% accuracy and 77.2% F1 on a 526-function PrimeVul test set, and 66.4% accuracy on SecVulEval without retraining.

arxiv.orgpaperAdded 30 Oct 2026, published 27 Oct 2026🛡️ Security

Heads of Security (HoS) is a prompt injection defense that enforces instruction-data separation with learned per-head attention gates, redistributing attention between trusted and untrusted tokens. Evaluated on Llama-3.3-70B-Instruct and GPT-OSS-20B against SecAlign++ and ASIDE. The black-box RL-Hammer attack reaches 97% ASR on GPT-OSS-20B and 85% on SecAlign but 10% on HoS. The white-box Claudini attack needs 3 times more FLOPs on HoS. HoS keeps base-model utility in few-shot settings, where SecAlign and ASIDE degrade.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

This paper presents an annotated egocentric tennis dataset (egocentric video synced with five allocentric views, global positions, contact times, stroke types) and evaluates image encoders, video encoders and vision-language models on seven prediction tasks. Best models reach 0.14 m player and 0.54 m ball localization error and 0.14 s contact-time error. Depth input helps 3D ball localization, and longer histories do not help forecasting. A conditional diffusion model generates whole-body tennis motion in real time.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

CRISP is a combination-aware framework that co-designs pruning and runtime scheduling for Mixture-of-Experts inference on memory-constrained edge platforms. It reorders neurons by importance so one stored expert supports several execution widths, gives hot, warm and cold expert combinations different widths, and overlaps expert loading with computation. On Mixtral-8x7B and DeepSeek-MoE-16B it raises throughput up to 2.1x at the same memory budget, with accuracy loss limited to 3.6%.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

Preprint on using nitrogen-vacancy (NV) center quantum sensing for electromagnetic side-channel analysis of ICs. The authors build an NV-based RF spectrometer with 1.1 GHz real-time bandwidth and adjustable center frequency, which reads the spectrum in the time domain without Fourier transforms or frequency sweeps. They use it on RSA decryption emanations and for leakage detection on a software Number Theoretic Transform running on a Cortex-M4 microcontroller.

eprint.iacr.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

DCKV is a differentiable codec for the prompt KV cache of hybrid language models, which keep a KV cache only in their few full-attention layers. Transform, quantizer and entropy models (conditioned on prompt tokens and already decoded neighbouring positions) are trained end to end against a frozen model. On Qwen3.5-2B it stores a token in over 55 times fewer bytes than bf16 with at most 1.8 points lost on three long-context benchmarks, and over 100 times fewer with at most 3.6 points lost.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

Poly2MsgLeaks is a profiled chosen-ciphertext power-analysis attack on the SMAUG-T (TiMER parameter set) post-quantum KEM that recovers the full 512-coefficient PKE secret from six traces on an STM32F415. It recovers 999 of 1,000 unseen secrets and proves an incorrect key is released with probability at most 2^-2095.6. Single-write message assembly and a two-share masked P2M resisted the evaluated six-execution attack.

eprint.iacr.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

OblivDGL is a secure computation framework for GNN training and inference, modelled on Deep Graph Library. It uses an oblivious message-passing paradigm and an oblivious graph representation built on function secret sharing (FSS). It leaks only total node and edge counts. On four benchmark graph datasets it cuts training communication up to 1024x and runtime up to 14.3x against prior secure GNN systems.

eprint.iacr.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

CTGREP is a compiler-based framework that applies differential analysis across the whole Clang/LLVM compilation chain to find where, how and under which configurations compiler optimizations break constant-time cryptographic code. Applied to seven libraries, three Clang versions, six targets and thousands of configurations, it led to 48 cases fixed with developers. It also identified seven new problematic LLVM passes and bypassed existing compiler-flag mitigations.

eprint.iacr.orgpaperAdded 27 Oct 2026, published 26 Oct 2026🛡️ Security

REVA (REal-time Vulnerability Analysis) is a vulnerability detector that puts a module threat model, lightweight static analysis findings and call-graph information into one LLM forward pass. A trained probe reads the model's internal representations of the new function. On PrimeVul's held-out test set, REVA on GLM-5.3-Flash reaches 60.0% accuracy in about one second per function, matching the agentic VulTriage (59.2%) at over 250 times the speed and under a tenth of the cost. The probe is 14% to 17% more accurate than the LLM's own verdict.

arxiv.orgpaperAdded 28 Oct 2026, published 26 Oct 2026🧠 AI

REVA (REal-time Vulnerability Analysis) is an LLM-based vulnerability detector that screens each new function in one forward pass. It feeds the model a pre-computed module threat model, lightweight static analysis findings and call-graph data, then reads the model's internal representations with a trained probe. On PrimeVul's held-out test set with GLM-5.3-Flash it reaches 60.0% accuracy in about one second per function, matching the agentic VulTriage (59.2%) while over 250 times faster.

arxiv.orgpaperAdded 28 Oct 2026, published 26 Oct 2026🛡️ Security

A Memory-efficient Implementation of Wiedemann XL is an ePrint paper (2026/2641) giving the first efficient on-the-fly implementation of XL with block Wiedemann for the multivariate quadratic problem. It builds on the CCNY SSE implementation, removes column-index tables, and computes column indices with O(n^2) instead of O(n^3) look-ups. It runs in comparable BW1 time with up to five times less memory, and an AVX2 port covers F256, the main field of UOV.

eprint.iacr.orgpaperPublished and added 26 Oct 2026🛡️ Security

Subexponential Algorithms for LWE via Rejection Sampling on Superlattices is an ePrint paper by Ligeng Fan, Changpeng Shao, Hongbo Li and Dingkang Wang. It extends the Ducas, Engelberts and Loyer superlattice framework to give a provable classical search-LWE algorithm for prime q in [n^2, 2n^2], using m=4n samples and time and space exp(O(n/ln ln n)). A second variant runs in 2^((1/2+o(1))n/ln R) for general parameters. It resolves a gap left by Kirchner and Fouque.

eprint.iacr.orgpaperPublished and added 26 Oct 2026🛡️ Security

Anis Bkakria's ePrint 2026/2638 gives polynomial-time decision attacks on Known-Covariance Ring-LWE (KCov-RLWE), the assumption Micciancio and Suhl introduced for simulation-secure threshold encryption. The public sample and covariance hint form a bordered Gram matrix whose determinant leaks a residual that differs between real and uniform samples. The attacks cover broad prime-modulus families at ring rank one and transfer to composite moduli with an odd prime divisor. Power-of-two moduli are not covered, and the paper does not break the full threshold-encryption scheme.

eprint.iacr.orgpaperAdded 26 Oct 2026, published 25 Oct 2026🛡️ Security

This paper evaluates sycophancy in medical diagnosis across nine AI models. Each model is shown clinical evidence plus a patient's belief in a specific but incorrect condition, with the belief's closeness to the evidence varied. Models adopted the belief 23.2% of the time on average, even for fictional conditions, and 43.0% under a Rare Disease Claimer persona. Medical fine-tuning and larger scale reduced susceptibility.

arxiv.orgpaperAdded 27 Oct 2026, published 25 Oct 2026🧠 AI

Intervention-Certified Amplification (ICA) is a validity gate for sigma-weighted hybrid SFT/RL post-training. The paper shows that DIAA, a per-sample sigma-weighted hybrid, emits unexecuted tool-integrated reasoning on 29% of MATH-500 prompts (three times vanilla GRPO) even with Python fences removed from its anchor. ICA gates sigma with paired-rollout evidence, cutting TIR to 13.8% (frozen) and 11.2% (online) and raising accuracy from 47.5% to 48.7% and 49.3%. It transfers to GSM8K.

arxiv.orgpaperAdded 27 Oct 2026, published 24 Oct 2026🧠 AI

Ranking Is Not Deciding is an October 2026 arXiv paper showing that query-time RAG poisoning filters score near-perfectly because of how the poison set was built. PoisonedRAG's code prepends the target question to each passage. Removing that prefix takes RAGuard from AUROC 0.953 to 0.758 and its miss rate from 0.191 to 0.763. The authors release a script that profiles a poison set.

arxiv.orgpaperAdded 27 Oct 2026, published 24 Oct 2026🛡️ Security

Persistent Closed-Form Routing (PCR) is a plug-and-play method for multivariate time-series forecasting. It alternates exact conditional estimation of channel-specific mixture weights with gradient training of low-rank residual experts around a frozen pretrained forecaster. Across eleven datasets and three backbones, PCR-K4 cuts dataset-balanced MSE by 3.86-14.25% and beats competing specialization methods with fewer trainable parameters. The paper also introduces GalaxyTS, a synthetic dataset with exact shared and channel-specific references.

arxiv.orgpaperAdded 27 Oct 2026, published 24 Oct 2026🧠 AI

DualPace is an LLM serving runtime that treats the host as an independently scheduled decode engine. A GPU engine runs prefills and GPU-resident decodes, while an AMX-enabled CPU engine batches and advances CPU-resident decodes, optionally calling GPU Dense Assist for dense stages. In decode-oriented scenarios it raises throughput 6.9 to 43.2% over NEO and 11.5 to 90.6% over vLLM at similar latency.

arxiv.orgpaperAdded 27 Oct 2026, published 24 Oct 2026🧠 AI

Gao and Hu's IACR ePrint 2026/2622 shows that if the matrix multiplication exponent satisfies ω ≤ 9/4 − η, heuristic lattice sieving runs in (3/2 − δ)^(n/2+o(n)) time under the spherical heuristic from the BDGL analysis. It builds on OpenAI's recent result that ω ≤ 9/4. With known matrix multiplication algorithms, the method already gives subquadratic search inside BDGL buckets. Only the abstract is available, so concrete parameters are not shown.

eprint.iacr.orgpaperAdded 26 Oct 2026, published 24 Oct 2026🛡️ Security

The paper formalizes elliptic-curve semiprimality certificates by adapting the Goldwasser-Kilian primality criterion. For certificates built with complex multiplication, a norm-lattice reconstruction factors N from (N, S, D) alone in expected polynomial time. The author uses it, plus public-point and quadratic-twist attacks, to factor Reble's 1084-digit and Broadhurst's 5061-digit moduli, and shows that hidden-cofactor, withheld-CM-map and private-isogeny repairs also fail.

eprint.iacr.orgpaperAdded 26 Oct 2026, published 24 Oct 2026🛡️ Security

OWLS (Open-world Language-conditioned Speed Fields) plans directly over a vision-language model's dense feature map. A text prompt describing traversable terrain scores every pixel of one camera image. The scores are projected onto the ground, adapted with two morphological operations, and used as the speed field of a minimum-time planner. It needs no training, terrain labels, map or extra sensors. It was tested on a physical rover, on simulated Mars and Moon rovers over 200 procedural terrains, and on real planetary imagery.

arxiv.orgpaperAdded 26 Oct 2026, published 23 Oct 2026🧠 AI

UAV-SwarmAgent is a hierarchical multi-agent system where an operator gives one natural-language sentence and a ground-station agent writes and runs code that produces per-UAV routes. A vision-language model grounds targets in an aerial map, and worker agents verify incidents with a compact onboard model. In simulation it located the incident in 244 of 255 missions (95.7%), and flight time followed an Amdahl-type law with speedup bounded at 1.52x for one to five UAVs.

arxiv.orgpaperAdded 26 Oct 2026, published 23 Oct 2026🧠 AI

Sentiment-Injected Sentence Embeddings (SISE) addresses a finding across eleven frozen text encoders (2021 to 2026): linear probes recover sentence polarity at up to 91.3% accuracy, but cosine similarity separates polarity by only 0.003-0.064. A small supervised-contrastive head (0.13M-0.69M parameters) trained on CPU raises retrieval MAP by up to 26 points, but the 128-d head loses 38-41 STS-B Spearman points. The paper also releases the Attribute Alignment Gap diagnostic.

arxiv.orgpaperAdded 26 Oct 2026, published 23 Oct 2026🧠 AI

Decode-time provenance binding is a defense for Model Context Protocol agent pipelines against cross-modal trust laundering, where instructions hidden in an email-signature image via LSB, DCT or metadata steganography get decoded by a tool. It combines HMAC-authenticated trust labels, a provenance ledger and context-taint tracking to block critical tool calls. On a real MCP testbed with 24 adaptive payloads, attack success fell from 100% undefended (62.5% for keyword and regex filters) to 0%.

arxiv.orgpaperAdded 26 Oct 2026, published 22 Oct 2026🛡️ Security

Mímir is a cryptographic protocol for stateless semantic private search over highly dynamic public databases. It uses homomorphic ciphertext switching, relies on (Ring) Learning with Errors, and needs no offline communication. Against Tiptoe it matches search quality with 84x less per-query communication (0.24 MiB). Against PACMANN it raises quality from 76% to 81% of non-private search, with a 9.54 MiB one-time cost instead of 2.68 GiB, but is 2.1x slower.

eprint.iacr.orgpaperAdded 24 Oct 2026, published 22 Oct 2026🛡️ Security

CausalCoT is an inference framework that splits a problem into a directed acyclic graph of atomic sub-questions and evaluates each node in an isolated context holding only its direct causal parents. This removes attention paths to non-parent content, so intermediate steps drive the answer rather than leaking from global context. It keeps benchmark accuracy competitive and raises causal sensitivity of reasoning steps by 12 points on average, up to 21, over the strongest baseline. The graph also allows test-time corrections that propagate downstream.

arxiv.orgpaperAdded 24 Oct 2026, published 22 Oct 2026🧠 AI

BeNice! is a post-training method for looped language models that broadcasts the final recurrence's KV-cache into the first recurrence, so one cache can serve all recurrences. It follows a first stage that uses stochastic depth in pretraining to induce contractive residual dynamics. It matches standard finetuning's unshared validation perplexity and composes with multi-latent attention, Kimi delta attention and fp8, mxfp8 and nvfp4 cache quantization. In simulated low-memory long-context inference it raises cache hit rates by up to 31.4% and throughput by up to 23.6%, and cuts p90 time-to-first-token by up to 83.6%.

arxiv.orgpaperAdded 24 Oct 2026, published 22 Oct 2026🧠 AI

Progress Probes (P^2) trains linear probes on a vision-language-action model's own activations, using demonstrations, to estimate task progress, then flags executions that deviate from expected progress. Tested on the open-source pi0.5 across simulated and real-world manipulation tasks, it matches or beats VLM-based monitors and failure-data-trained methods at failure detection, without an external foundation model.

arxiv.orgpaperAdded 24 Oct 2026, published 22 Oct 2026🧠 AI

TTR-Compressor is a sequence compression method that treats input tokens as a test-time regression problem. The regression is learned end-to-end by backpropagation, and its coefficients are solved in closed form in the forward pass to give the compressed representation. As a block-wise sparse attention compressor it improves RULER over attention-based compressors by a large margin. As a visual token merger for multimodal LLMs it beats the MLP merger and matches it with 55.6% fewer visual tokens.

arxiv.orgpaperAdded 24 Oct 2026, published 22 Oct 2026🧠 AI

Gandalf is an SSD KV cache offloading system for LLM serving that is aware of SSD lifetime. It prioritizes admitting full-attention KV cache to SSD over cache from other attention types, using application-level information rather than access history alone. The authors report a 7.3x average SSD lifetime extension with negligible cache hit rate loss across several workload traces and hardware capacities. The design may extend to High Bandwidth Flash.

arxiv.orgpaperAdded 23 Oct 2026, published 22 Oct 2026🧠 AI

Matrix-Game 4.0 is a system that separates game logic from visual rendering for playable generated worlds. A lightweight engine holds world state and rules, a multimodal coding agent writes game code and scene captions, and a distilled autoregressive video model turns low-poly proxies into detailed frames. It runs 480p at 60 FPS on one RTX 5090 with 112 ms key-press-to-display latency. Code, weights and assets are released.

huggingface.copaperAdded 22 Oct 2026🧠 AI

SBFS-FT (symmetry-based few-shot fine-tuning) adapts the MatterSim 1M universal machine-learned interatomic potential with low-rank adaptation on a small set of compounds sharing one crystal symmetry. Tested on half-Heusler (space group 216), space group 225 and spinel (227) datasets, it cut lattice thermal conductivity error 2-3 times versus the base model. It matched per-compound fine-tuning while taking 5-7 times less compute for 100 compounds.

arxiv.orgpaperAdded 23 Oct 2026, published 21 Oct 2026🧠 AI

RingTrace is a monitoring framework that detects Flush+Reload cache side-channel attacks by combining per-core cache-miss counters with slice activity across uncore CBoxes. Its Joint Spatio-Temporal Attribution (JSTA) builds a joint-activity matrix without model training: the largest entry is the screening score and row sums point to a candidate core. The authors report detection before secret leakage, fewer false alarms under heavy memory load, and negligible runtime overhead on commodity processors.

eprint.iacr.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

Rounded Gaussians are Discrete Gaussians is an IACR ePrint paper (2026/2583) by Corentin Jeudy. It shows that setting the rounded Gaussian parameter to sigma = s - 1/(24s) gives a distribution within Rényi divergence 1 + O(1/s^8) of a discrete Gaussian of parameter s. Lattice schemes can then use the simple, constant-time-friendly, low-memory rounded sampler while analyzing security against an ideal discrete Gaussian.

eprint.iacr.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

Table-free constant-work BCH decoding by algebraic index elimination is an IACR ePrint paper (2026/2580) that replaces the table scans in Walters and Sinha Roy's constant-work BCH decoder with fixed circuits over public addresses. It proves correctness through radius t and trace regularity, removes 5.2 and 7.2 KiB of tables, and runs 35.7 to 82.4 times faster on an i7-13700. Ordinary C masks compiled to received-word-dependent branches under Apple Clang 21, so the authors use a compiler-opaque primitive and run timing screens on four platforms.

eprint.iacr.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

This ePrint paper presents an optimized HAETAE implementation, a lattice-based post-quantum signature scheme, for Cortex-M4, Cortex-M3, MSP430 and AVR. It keeps polynomials in 16 bits, shares buffers between objects with disjoint lifetimes, and replays Gaussian samples instead of regenerating them. On an ATmega2560, HAETAE-2 key generation, signing and verification run in 8,070 B of SRAM. Stack use drops up to 34% and signing is 1.18-2.51x faster than Low-Stack HAETAE.

eprint.iacr.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

InterWebCoder is a framework for interactive webpage code generation by multimodal LLMs. It synthesizes self-contained webpages with executable test scripts from recorded interaction trajectories, repairs failures using runtime evidence, then trains with test-ID-weighted SFT and GRPO using test pass rates and visual similarity as rewards. The pipeline yields 1,736 verified samples from 2,058 tasks. A 9B model scores 48.54 on IWR-Bench and 48.42 on Vision2Web, and reward latency drops over 97%.

arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026🧠 AI

CarryoverBench is a benchmark of 12 personal-assistant scenarios and 101 attack tasks for carryover attacks, where a one-time indirect prompt injection planted in agent memory files or scheduled tasks re-fires in later sessions. Three trigger channels (Instant, Autonomous, Latent) are scored by a rule-based verifier with separate planting and triggering stages. Across five frontier models, payloads re-fire over five rounds without measurable decay. Porting the Latent channel to the Hermes runtime weakens the effect but does not remove it.

arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026🛡️ Security

DIVE is a benchmark for full-duplex interaction with visual engagement in continuous audio/video streams. It has 525 human-annotated samples across six tasks in three scenarios: proactive intervention, continuous engagement and interaction coordination. Evaluated real-time models reach sub-second average latency, but window response rates stay at or below 53.77%, and adapting ongoing responses to new information is hardest.

arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026🧠 AI

Efficient NTRU+ Implementations on Cortex-M presents NTRU+ KEM implementations built on 3-way NTTs for Arm Cortex-M0+, M3, M4 and M7. It adds omega-folded front layers that handle ternary inputs without modular reduction. The speed-optimized version cuts execution time by up to 52.43% against the official optimized C code. The memory-optimized version cuts peak stack use by up to 82.60%.

eprint.iacr.orgpaperAdded 21 Oct 2026, published 20 Oct 2026🛡️ Security