Search: “context”

Working Around the Compute Ceiling: Byte-Exact Memory in Galahad Makes LLM Reading a One-Time Cost LLM Reading a One-Time Cost

arXiv:2609.39358v1 Announce Type: cross Abstract: A transformer language model performs a bounded amount of computation per token, and recent work by Vishal Sikka, former CEO of Infosys, argues that t

1 Oct 2026

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World-as-Graph: Relational World Modeling Through Latent Space Graphs

DGX agent

arXiv:2609.38927v1 Announce Type: cross Abstract: World models aim to learn representations of real-world environments and predict their future evolution. Recent object-centric world models have made

safetyarxiv-cs-cv

1 Oct 2026

Act First, Reason Later: Accelerating On-Policy Distillation for Multi-Turn Agents via Reference-Conditioned Inverse Dynamics

model-releasesarxiv-cs-cl

arXiv:2609.36608v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains multi-turn language agents with dense teacher supervision on student-generated responses. However, standard think-

Adaptive Consistency Graph for Long-Horizon Agents

arXiv:2609.32754v2 Announce Type: replace Abstract: Large language model agents can often make reasonable local decisions on short tasks, yet their performance degrades when success requires long sequ

Boundary-State Control for Tool-Using Language-Model Agents: Commit-Time Consistency under State Drift

arXiv:2609.37475v1 Announce Type: new Abstract: Tool-using language-model agents can decide that an action is permissible and execute it only after security-relevant state has changed. We study this p

safetyarxiv-cs-ai

CADENCE: A Confidence-Adaptive Dual-Expert Network for Fast and Accurate Time Series Classification

arXiv:2609.35929v1 Announce Type: new Abstract: Time series classification (TSC) exhibits a sharp trade-off between accuracy and computational scalability. Meta-ensembles like HIVE-COTE 2.0 reach stat

Can Language Models Learn to Forecast Stock Prices

model-releasesarxiv-cs-cl

arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning,

CineSubBench: Evaluating LLMs on Long-Form Narrative and Cultural Understanding from Multilingual Movie Subtitles

arXiv:2609.36218v1 Announce Type: cross Abstract: Large language models are increasingly evaluated in specialized domains such as law, medicine, software engineering, and cybersecurity, yet film remai

Data-Efficient Time-Dependent PDE Surrogates: Graph Neural Simulators vs. Neural Operators

arXiv:2509.06154v3 Announce Type: replace Abstract: Developing accurate, data-efficient surrogate models is central to advancing AI for Science. Neural operators (NOs), which approximate mappings betw

local-aiarxiv-cs-lg

Does the Unsafe Gradient Survive a Conversation? On the Fragility of Gradient-Based Jailbreak Detection in Multi-Turn Dialogue

arXiv:2609.36849v1 Announce Type: cross Abstract: Safety-aligned language models are commonly deployed as multi-turn assistants, which lets adversaries spread unsafe intent across several user turns i

Agents

doPlan: A Variable-Horizon Dataset for Multi-Stage Language-Conditioned Planning in Autonomous Driving

arXiv:2609.38028v1 Announce Type: cross Abstract: Autonomous vehicles interacting with passengers through natural language must reason beyond immediate commands. Passenger intent may span multiple sta

agentsarxiv-cs-ai

DSPO: Diversity-aware Subjective Policy Optimization for Robust Emotional Reasoning

arXiv:2609.36775v1 Announce Type: new Abstract: Reinforcement Learning has significantly advanced the complex reasoning capabilities of MLLMs. However, prevailing RL algorithms suffer a severe failure

Efficient and Scalable Physics-Guided Fully Convolutional Spatiotemporal Learning for 3D Microstructure Evolution Prediction

arXiv:2609.36504v1 Announce Type: new Abstract: Accurate prediction of three-dimensional (3D) microstructure evolution remains computationally demanding because high-fidelity phase-field simulations r

local-aiarxiv-cs-lg

Evaluating the Effects of Prompt Perturbation on Bias and Hallucination in Large Language Models

arXiv:2609.35804v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable capabilities in various natural language processing tasks, leading to their widespread deployment a

EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception

arXiv:2609.37123v1 Announce Type: new Abstract: Fine-grained visual perception enables vision-language models to distinguish subtle attributes and ground their answers in visual evidence. In high-reso

researcharxiv-cs-cv

Generating Edit-Inducing Questions for AI Research Manuscripts

arXiv:2609.36617v1 Announce Type: new Abstract: We study the ability of LLMs to generate edit-inducing questions whose answer will improve a paper draft. On a dataset of paired submission and camera-r

researcharxiv-cs-cl

Generative Interactions: Weaving Multiparty Human Motion with Bilevel Latent Dynamics

arXiv:2609.37708v1 Announce Type: new Abstract: Human social behaviour is not a collection of independent motions, but a jointly organised process in which group dynamics and individual variation cont

safetyarxiv-cs-ai

GNA: Granular Neighbor Assembly for Retrieval-Augmented Multivariate Time-Series Forecasting

arXiv:2609.36281v1 Announce Type: new Abstract: Deep forecasters predict from a fixed-length lookback window, and lengthening it gives diminishing returns at a growing cost. Retrieval augmentation ins

Graph-Spectral Flow Matching for Multivariate Time Series Anomaly Detection

arXiv:2609.36765v1 Announce Type: new Abstract: Multivariate time series anomaly detection typically relies on evaluating discrepancies between observations and outputs produced by models trained on n

High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching

arXiv:2609.37037v1 Announce Type: new Abstract: High-resolution dynamic functional connectivity (DFC) can reveal rapidly evolving brain-network interactions, but short temporal windows yield noisy, of

How Language Models Differ in Redistributing Attention-Head Activity Under Serial Demand

model-releasesarxiv-cs-lg

arXiv:2609.36221v1 Announce Type: new Abstract: The way a model distributes activity over each layer's attention heads offers a coarse view of how it routes information through depth; how this changes

Hybrid Ensemble Learning for EEG-Based Epileptic Seizure Forecasting

arXiv:2609.35876v1 Announce Type: new Abstract: Epileptic seizure forecasting aims to provide actionable warnings before seizure onset, yet patient-independent generalization and false-alarm control r

LazySloth: Bounded LLM-based Lazy Tree Search for Fast Long Video Comprehension

arXiv:2609.37426v1 Announce Type: cross Abstract: Modern vision-language models (VLMs) have shown promising results in long-video understanding due to the rich semantic information they can capture. H

LeapQuant: Efficient Linear Attention with Accurate Recurrent State Quantization

arXiv:2609.38166v1 Announce Type: cross Abstract: Recent LLMs increasingly adopt hybrid designs that replace standard attention with linear attention, such as Gated DeltaNet (GDN) and Kimi Delta Atten

Locating Answer-Correctness Signals in Frozen Large Language Models

arXiv:2609.37700v1 Announce Type: new Abstract: Language models expose internal signals that predict whether an answer is correct, readable from a single forward pass of a frozen model without additio

researcharxiv-cs-ai

MVG-WAM: Multiple View Geometry-Aware World-Action Modeling for Robotic Manipulation

arXiv:2609.37793v1 Announce Type: new Abstract: World-Action Models (WAMs) couple visual dynamics with action prediction, bringing the rich priors of pretrained video models to robotic manipulation. H

local-aiarxiv-cs-ro

PACT: Pairwise-Anchored Calibrated Tuning for Single-Token Typed Decisions

arXiv:2609.35865v1 Announce Type: cross Abstract: Single-token typed-decision models answer a schema question by reading the logits of a few one-letter answer codes at a single position: they are fast

Physical Cross-Modal Masked Autoencoding for Seismic-to-Well Representation Learning

arXiv:2609.36193v1 Announce Type: new Abstract: Learning from scientific measurements often requires aligning modalities with different spatial support and resolution. Subsurface characterization is a

QuantMLA: Function-Aligned Dual-Path Quantization for Low-Bit MLA KV Caching

model-releasesarxiv-cs-cl

arXiv:2609.36760v1 Announce Type: cross Abstract: Multi-Head Latent Attention (MLA) enables expressive multi-head attention with compact caches for its content and decoupled RoPE paths, yet cache memo

ReCaVSR: One-Step Streaming Diffusion Video Super-Resolution with Recycled Latents and Learned Cache Routing

arXiv:2609.37831v1 Announce Type: new Abstract: Real-time diffusion-based video super-resolution (VSR) is in high demand for online streaming, yet stringent latency requirements often compromise gener

local-aiarxiv-cs-cv

Regime Boundary Alignment for Evidence-Gated Question Answering

arXiv:2609.37491v1 Announce Type: cross Abstract: Retrieval-augmented language models are expected to answer from the retrieved evidence, but in practice they often keep answering when that evidence i

safetyarxiv-cs-ai

Reliable Parallel Decoding in Masked Diffusion Language Models

arXiv:2609.36452v1 Announce Type: cross Abstract: Masked diffusion language models (MDLMs) can generate text efficiently by predicting multiple masked tokens in parallel, but predictions from the same

researcharxiv-cs-ai

RS-OPSD: Reliable Privileged On-Policy-Self-Distillation for Ultra-High-Resolution Remote Sensing VQA

arXiv:2609.38072v1 Announce Type: new Abstract: Ultra-high-resolution (UHR) remote sensing visual question answering (VQA) requires models to resolve small visual evidence within extremely large image

Scene Retargeting: Learning Object Placement with Analogical Transfer

arXiv:2609.36801v1 Announce Type: new Abstract: Interactive simulations of embodied AI or spatial computing applications build on realistic 3D scenes that support daily activities. However, sparse, ir

Agents

Selective Elicitation as a Commercial Influence Channel: A Reproducible Synthetic Shopping-Agent Stress Test

arXiv:2609.36614v1 Announce Type: new Abstract: A commercial incentive need not enter the final ranking algorithm to affect a shopping assistant's recommendation: it may instead influence which prefer

agentsarxiv-cs-lg

The Surge of Anti-Semitism in German Social Media following the October 7 Attacks

arXiv:2609.36290v1 Announce Type: cross Abstract: We investigate the extent to which the Hamas attacks on Israel of October 7, 2023, have affected German social media debates about Judaism and Israel.

researcharxiv-cs-cl

Understanding Private Evolution as Learning-Augmented Clustering

arXiv:2609.36678v1 Announce Type: new Abstract: Private Evolution (PE) is a differentially private algorithm for synthetic data generation. While it can be viewed as a Wasserstein learning algorithm,

VideoLoop: Looped Working Memory Against Semantic Thrashing in Long-Form Video Agents

model-releasesarxiv-cs-cv

arXiv:2609.38119v1 Announce Type: new Abstract: Long-form video understanding requires multimodal agents to iteratively gather evidence over many reasoning steps. However, most existing agentic method

When Successful Memories Mislead Embodied Agents:Memory Adaption For Task-Conditioned Execution

arXiv:2609.35808v1 Announce Type: cross Abstract: Experience reuse can reduce repeated exploration in embodied agents, but a trajectory that succeeded previously may be unsuitable for the current exec

researcharxiv-cs-ai

Beyond Timestamps: Decision-Aligned On-Policy Distillation for Long-Horizon Agents

arXiv:2609.33391v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) often relies on sparse outcome rewards, providing coarse supervision for long-horizon agents. On-p

safetyarxiv-cs-lg

CT-OPD: Counterfactual Trace On-Policy Distillation for Diffusion Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.32781v1 Announce Type: new Abstract: Diffusion vision-language models generate answers by gradually resolving masked tokens, making accurate conditional prediction in partially resolved sta

Agents

CueKFS: Agentic Cue-Driven Keyframe Selection for Long Video Understanding

arXiv:2609.31873v1 Announce Type: new Abstract: Keyframe selection (KFS) has long produced compact video summaries for browsing and retrieval, and representative frames for thumbnails. More recently,

agentsarxiv-cs-cv

DRAM: Delta-rule Recurrent Associative Memory for Robot Manipulation Policies

arXiv:2609.32453v1 Announce Type: new Abstract: Robotic manipulation is inherently history-dependent, yet most pretrained robotic policies condition on only the current observation or a short temporal

safetyarxiv-cs-ro

Hardware

From Experience to Expertise: Adoption-Aware Memory Learning for Data-Scarce NPU Kernel Synthesis

arXiv:2609.35568v1 Announce Type: new Abstract: High-performance kernels underpin efficient accelerator execution but require expert tuning and lengthy manual optimization cycles. LLM coding agents pr

hardwarearxiv-cs-lg

From PDF to Evidence: Structure-Aware Retrieval for Clinical Practice Guidelines

arXiv:2609.33447v1 Announce Type: cross Abstract: Guideline documents are published as unstructured PDFs whose evidence is locked in visual structures---tables, flowcharts, and graded recommendations-

researcharxiv-cs-cv

How Linear Attention Remembers

arXiv:2609.33093v1 Announce Type: new Abstract: Linear attention replaces the growing key--value (KV) cache of standard attention with a fixed-size recurrent state, substantially reducing memory growt

Just-In-Time Agent Memory with Runtime Agentic Research

arXiv:2609.34385v1 Announce Type: cross Abstract: Memory is critical for AI agents. Many existing agent-memory systems follow an Ahead-of-Time (AOT) design, constructing memory before a specific reque

safetyarxiv-cs-lg

Mask2Restore: Self-Supervised Ultrasound Despeckling via Inpainting

arXiv:2609.32844v1 Announce Type: cross Abstract: Medical ultrasound (US) is inherently degraded by speckle, a granular interference pattern that is often treated as a complex form of noise in image r