Search: “context”

RoboFoundry: System-as-Policy Evolution for Self-Learning Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2609.32862v1 Announce Type: new Abstract: A foundation model should not act in isolation as an embodied agent. Yet, existing methods often optimize individual components of the agent stack, such

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RoboIRGBench: Benchmarking Implicit Referential Grounding in Vision-Language-Action Models

DGX agent

arXiv:2609.34384v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in robotic manipulation, yet existing benchmarks typically assume that task-relevan

model-releasesarxiv-cs-cv

29 Sept 2026

Robot-Assisted Deployment and Maintenance of Inflatable Modules for Lunar Habitation: A Field Demonstration

arXiv:2609.34498v1 Announce Type: new Abstract: Long-term human habitation and in-situ development on the Moon open a new era of space utilization. In this context, robots are a key technology for fac

The Earth in One Gaze: Training-Free Active Focus for UHR Remote Sensing Understanding

arXiv:2609.31747v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) must balance local detail against scene context when interpreting ultra-high-resolution (UHR) remote sensing (R

The Temporal Tug-of-War: Visualizing and Detecting RAG Conflicts in Diffusion Models via Trajectory Variance

arXiv:2609.31684v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) introduces a specific failure mode in discrete diffusion language models: when retrieved context contradicts para

researcharxiv-cs-lg

TokenCast: Forecasting Token Consumption During LLM Agent Execution

arXiv:2609.35760v1 Announce Type: new Abstract: When a large language model (LLM) agent executes the same task, token consumption can vary by over an order of magnitude across runs. The agent chooses

safetyarxiv-cs-lg

UniCache: Task- and Type-Aware KV Cache Compression for Unified Multimodal Models

arXiv:2609.32831v1 Announce Type: new Abstract: Unified multimodal models combine understanding, generation, and editing within a single network, offering a promising foundation for versatile multimod

safetyarxiv-cs-lg

UNMATCH: Selective Unbalanced Token-Patch Matching for Forensic Image-Claim Verification

arXiv:2609.31766v1 Announce Type: new Abstract: Contextual image misuse pairs an image with a misleading claim. We study image-claim correspondence in fact-checked pairs containing out-of-context reus

Local Ai

What Should Data Teach? Moving Bottlenecks Across Circuit, Store, and Use

arXiv:2609.32991v1 Announce Type: new Abstract: What should data teach a language model at a particular point in training? A circuit view reveals three distinct bottlenecks: forming a computation, mak

local-aiarxiv-cs-lg

When Does Structured Knowledge Help Neural Theorem Proving?

model-releasesarxiv-cs-lg

arXiv:2609.34460v1 Announce Type: cross Abstract: Does structured mathematical knowledge help LLMs prove theorems in Lean 4? If so, for which models, and does the answer vary by problem? Formal librar

When Retrieval Hurts: Measuring and Explaining Retrieval-Induced Hallucination in Chest X-ray Report Generation

arXiv:2609.31733v1 Announce Type: new Abstract: Retrieval-augmented generation is an attractive way to improve chest X-ray reporting, because reports from similar prior studies supply clinical context

researcharxiv-cs-cv

X-MoD: Practical Scaling Laws for Sparse-Depth Routing Beyond Mixture-of-Depths

model-releasesarxiv-cs-lg

arXiv:2609.34212v1 Announce Type: new Abstract: Mixture-of-Depths (MoD) enables conditional computation across Transformer depth by routing only a subset of tokens through selected layers, but its ori

Acoustic-to-Text KV Compression for Full-Duplex Speech Models

arXiv:2609.31224v1 Announce Type: cross Abstract: Full-duplex speech language models continuously accumulate acoustic key-value (KV) states, making long-running interactions memory-intensive. During l

Audio emotion recognition for atypical hearing

arXiv:2609.31168v1 Announce Type: new Abstract: My doctoral work aims to explore Audio Emotion Recognition (AER) in the context of atypical listening. This research focuses on auditory hypersensitivit

researcharxiv-cs-lg

Cartograph: Federated Tool Discovery with Operator-Attested Retrieval for AI Agents

arXiv:2609.30293v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) enables AI agents to discover and call tools, but loading every definition becomes expensive as connected catalogs gr

Combee: Scaling Prompt Learning for Self-Improving Language Model Agents

arXiv:2604.04247v2 Announce Type: replace Abstract: Recent advances in prompt learning allow large language model agents to acquire task-relevant knowledge from inference-time context without paramete

Does Uniform Discrete Diffusion Need Time?

arXiv:2609.30977v1 Announce Type: cross Abstract: Uniform discrete diffusion models (UDMs) commonly use explicit time conditioning, but we find that it can often be unnecessary in practice. In this pa

Evaluation Is All You Need for Multi-Modal Autonomous Driving

arXiv:2609.30818v1 Announce Type: cross Abstract: Multi-modal planning is promising for autonomous driving by representing multiple plausible behaviors in ambiguous and long-tail scenarios. Existing m

safetyarxiv-cs-ai

FTB Graph: Determining and Validating First-token Broadcasters and Language-Identity Head Circuits in Multilingual Language Models

arXiv:2609.30954v1 Announce Type: new Abstract: Large language models operating in multilingual contexts must resolve target response languages early in generation, yet the causal circuitry governing

MedHal: a Synthetic Dataset for Medical Hallucination Detection

arXiv:2504.08596v3 Announce Type: replace-cross Abstract: Hallucination, the generation of non factual content by AI systems, poses serious risks in medical contexts, where errors can directly affect

Agents

PIA: A Personal Intelligence Agent Turning Health Conversations into Records and Records into Understanding

arXiv:2609.31255v1 Announce Type: new Abstract: General-purpose agent memory summarizes conversations: it extracts salient snippets, embeds them, and retrieves the top-k into the prompt. A health agen

agentsarxiv-cs-cl

Privacy-Preserving Prompted Policy Search for Robotic Control

arXiv:2609.30554v1 Announce Type: new Abstract: Large language models (LLMs) have recently demonstrated promising capabilities as in-context policy optimizers for Reinforcement Learning (RL), enabling

SkillFlow: Scalable and Efficient Agent Skill Retrieval System

arXiv:2504.06188v3 Announce Type: replace Abstract: AI agents can extend their capabilities at inference time by loading reusable skills into context, yet equipping an agent with too many skills, part

SoGuDiff: Socially Guided Diffusion for Steerable, Norm-Grounded Robot Navigation

arXiv:2609.30560v1 Announce Type: new Abstract: Beyond collision avoidance, socially competent robot navigation requires adherence to implicit social conventions that vary across contexts, cultures, a

tutorialsarxiv-cs-ro

Adversarial Closed-Loop Curriculum for Evolving Role-Playing Agents

arXiv:2609.28609v1 Announce Type: new Abstract: Role-playing agents based on large language models have been widely applied in areas such as personalized assistance and social simulation. Recent RL me

From Graphs to Feeders: Constraint-Guided Diffusion for Rule-Compliant Feeder Generation

arXiv:2609.29879v1 Announce Type: new Abstract: Generative modeling approaches often focus on recovering broad statistical characteristics from the training data. In the context of graph generation, t

researcharxiv-cs-lg

GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI

arXiv:2609.30147v1 Announce Type: new Abstract: Large Language Models (LLMs) typically exhibit a performance profile where reliability degrades as task complexity increases. We address the challenge o

Learning New Words from Unlabeled Test Data in Automatic Speech Recognition

arXiv:2609.28877v1 Announce Type: cross Abstract: New words are invented every day. A human listener can learn a new word by hearing it clearly once and inferring its usage from sentence context. This

tutorialsarxiv-cs-cl

UO-FIE: Combining Exact-Label Supervision with Graded Utility for Factivity Inference

arXiv:2609.28605v1 Announce Type: cross Abstract: The Factivity Inference Evaluation 2026 (FIE2026) classifies Chinese context-hypothesis pairs into nine ordered factivity intervals. Its evaluation me

Visual Representation and History Modeling for Navigation World Models

arXiv:2609.29555v1 Announce Type: new Abstract: Navigation World Models (NWMs) predict action-conditioned visual futures for planning. Two practical challenges are central to their design: selecting a

researcharxiv-cs-cv

Agents

When Fancy Eviction Fails: Rethinking Cache Replacement For LLM Prefix Reuse

arXiv:2609.28870v1 Announce Type: cross Abstract: Long-running LLM applications repeatedly send growing context, making prefix caching critical for reducing prefill cost. Yet prefix-cache behavior und

agentsarxiv-cs-lg

Attention Routing Stabilizes Early: Working-Set Inference for Recurrent Language Models

arXiv:2609.27373v1 Announce Type: new Abstract: Recurrent language models repeatedly apply shared network blocks to refine latent representations, but standard inference recomputes global attention at

researcharxiv-cs-cl

Benchmarking Active Spot Selection for Cost-Efficient Spatial Transcriptomics

arXiv:2609.27208v1 Announce Type: new Abstract: Spatial transcriptomics (ST) measures gene expression in tissue context, but dense capture grids can be costly and may repeatedly sample morphologically

Can Vision-Language Models Analyze Human-Centered Video? Mapping Model Capabilities and Human-AI Collaborative Workflows

arXiv:2609.27327v1 Announce Type: new Abstract: Video provides a rich record of human behavior, interaction, and situated contexts, offering important evidence for understanding people and conducting

DeltaS: Reading the Gated Linear Attention State for KV Cache Eviction in Streaming Video

model-releasesarxiv-cs-cl

arXiv:2609.27470v1 Announce Type: cross Abstract: Recent video-language models increasingly adopt hybrid architectures that interleave linear and full attention layers for efficient long-context proce

Distilling Sequential Computation in Transformer Language Models

arXiv:2609.27233v1 Announce Type: new Abstract: Transformer language models process sequences token by token in an autoregressive manner, making growing contexts increasingly expensive. Yet many adjac

researcharxiv-cs-cl

MemBodied: Recurrent Associative Memory for Vision-Language-Action Models

arXiv:2609.28256v1 Announce Type: cross Abstract: Vision-Language-Action models provide a strong foundation for general-purpose robot control, yet a vast majority of policies do not preserve and lever

safetyarxiv-cs-ai

MolDesignBench: Evaluating LLM-based Agent for Scenario-grounded Molecular Design

arXiv:2609.27349v1 Announce Type: new Abstract: Real-world molecular design remains challenging for large language model (LLM)-based agents. It requires them to interpret design contexts, satisfy mult

NPBoost: Neural Processes with Gradient-Boosted Fixed Effects

arXiv:2609.28122v1 Announce Type: cross Abstract: Neural Processes (NPs) are model-based meta-learners that implicitly learn a stochastic process and adapt to a new task from a small context set. Most

tutorialsarxiv-cs-lg

Agents

RegenHarness: A Robot Agent Harness with Evidence-Gated Recursive Self-Improvement

arXiv:2609.27612v1 Announce Type: new Abstract: Long-horizon robot execution requires a clear distinction between a model's proposal, a controller's termination, and verified task completion. We prese

agentsarxiv-cs-ro

Watch, Recall, Act: Always-On Robots in Concurrent Embodied Streams

arXiv:2609.28429v1 Announce Type: new Abstract: An always-on robot faces an endless stream that never resets: instructions arrive and lapse, the scene changes, and its own past actions reshape what it

A JEPA Recipe for Tabular Foundation Models

model-releasesarxiv-cs-lg

arXiv:2609.25541v1 Announce Type: new Abstract: Tabular foundation models learn to predict cell values in context, whereas world-model self-supervision asks for prediction in representation space (LeC

ClusterFewshot: Improving Few-shot Optimization for LLMs workflow

arXiv:2609.25939v1 Announce Type: new Abstract: The performance of large language model (LLM) workflows often depends on selecting a small set of in-context demonstrations to guide model behavior on n

tutorialsarxiv-cs-cl

Qwen3.8-Omni: Towards Native Omni-Modal Agents

model-releasesarxiv-cs-cl

arXiv:2609.25611v1 Announce Type: new Abstract: We introduce Qwen3.8-Omni-Flash, a natively multimodal agentic model for real-world multimodal productivity. Compared with previous omni models, which p

Reasoning Topology Matters: A Controlled Study of LLM-Based Cybersecurity Analysis

arXiv:2609.24710v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in cybersecurity, where accurate analysis often requires multi-step and context-dependent reasoning

Shaft-Configuration-Adaptive Catheter Tip Position Estimation via Motor-History Conditioned Residual Learning

arXiv:2609.26304v1 Announce Type: new Abstract: Tendon-driven continuum manipulators are widely used in medical applications, where accurate tip-position estimation is essential for precise navigation

researcharxiv-cs-ro

STRUCTUREDAGENT: Planning with AND/OR Trees for Long-Horizon Web Tasks

arXiv:2603.05294v3 Announce Type: replace Abstract: Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behavior

Zephyron: Integrated Design and Analytical Evaluation of a Solar-Assisted Mobile Manipulator for Multimodal Environmental Reconnaissance and Distributed Visual Inference

arXiv:2609.25709v1 Announce Type: new Abstract: Environmental reconnaissance needs mobile platforms that carry sensors, preserve measurement context, and return interpretable evidence under limited en