Search: “context”

Measure Learning at Steady State: A BIRD-SQL Formula 1 Case Study

arXiv:2609.31640v1 Announce Type: new Abstract: Continual Learning Bench scores learning as short-horizon gain versus a reset baseline and finds naive full-context ICL strongest among the memories it

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Probe to Act: Elevating Browser-Use Agent via Active Visual Probing

DGX agent

arXiv:2609.33646v1 Announce Type: cross Abstract: Browser-use agents require seamless alignment between structured web metadata and visual information, while preserving relevant context across long in

model-releasesarxiv-cs-cv

29 Sept 2026

Hardware

SANTA++: Sampling Attention through Representative Keys

arXiv:2609.35629v1 Announce Type: new Abstract: Attention often concentrates on a small subset of tokens in the context, but which subset matters changes from one query to the next. To exploit this ch

hardwarearxiv-cs-lg

When Keywords Drop but Classifiers Hold: Soft Refusals under KV Cache Compression

arXiv:2609.31678v1 Announce Type: new Abstract: KV cache compression is widely used for long context LLM inference under memory constraints, while deployed systems typically score refusals after gener

Where Activation Sparsity and KV-Cache Sparsity Cross in LLM Decoding

arXiv:2609.33889v1 Announce Type: new Abstract: At each step, decoding one sequence with a large language model rereads the projection weights, whose traffic is fixed, and the key-value (KV) cache, wh

safetyarxiv-cs-lg

HasMem: Hard-Origin Adaptively Softened Memory for Long-Term LLM Agents

arXiv:2609.30797v1 Announce Type: new Abstract: Text-based memory and context compression support reuse of past interactions. Resizing continuous memory changes the input to a frozen LLM, coupling cap

28 Sept 2026

TISD: On-Policy Self-Distillation with Trajectory Intervention

arXiv:2609.30878v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) provides dense teacher targets, but evaluates them only along student-sampled rollouts. When the privileged teacher f

safetyarxiv-cs-ai

28 Sept 2026

Agentic Detection of Online Conspiracies

arXiv:2609.30250v1 Announce Type: new Abstract: Conspiratorial discourse on social media is not always expressed through explicit claims or stable lexical markers. The same surface content may express

agentsarxiv-cs-cl

25 Sept 2026

ChunkRank: Model-Aware Text Chunking and Abstention-Aware Answer Selection for LLM Pipelines

arXiv:2609.29828v1 Announce Type: new Abstract: We present ChunkRank, an open-source Python library that derives chunk boundaries from a target model's tokenizer and context window, and selects an ans

25 Sept 2026

Self-Adaptive VLA for Robust Robot Deployment

arXiv:2609.30092v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models demonstrate impressive capabilities in robotic manipulation, their memoryless nature renders them brittle to

safetyarxiv-cs-cv

25 Sept 2026

Alignment of LRMs via Counter-Aligned Few-Shot Conversation Exposure

arXiv:2609.27763v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) rely on explicit chain-of-thought (CoT) reasoning and large context windows to achieve strong performance on complex tasks

safetyarxiv-cs-ai

24 Sept 2026

AgentBetta: Verification-Driven Adaptive Configuration of an AI Nano-Agent through Selective Expansion and Verified Contraction

arXiv:2609.23512v1 Announce Type: new Abstract: Large language model agents are typically deployed with predefined configurations, although the required model capability, context, tools, permissions,

Et Tu, Brute? Economic Misalignment in Personal AI Agents

arXiv:2609.24927v1 Announce Type: new Abstract: Personal AI agents make recommendations and take actions on people's behalf in high-stakes economic contexts, e.g., buying a flight, choosing health ins

SelfOp: An Optimization Algorithm for Self-Improving Security Agents

arXiv:2609.22792v1 Announce Type: cross Abstract: LLM agents are increasingly used for security tasks: vulnerability discovery, exploit reproduction, and patch generation. Improving them at the model

WorkWorlds: An Infrastructure for Evaluating AI Agents on Workplace Tasks

arXiv:2609.23806v1 Announce Type: new Abstract: Many knowledge-work benchmarks are constructed around individual tasks, with the context needed for each task selected together with or after the task h

agentsarxiv-cs-ai

Tutorials

RACER: Role-Aligned Competence Estimation for Human-AI Routing

arXiv:2609.21953v1 Announce Type: new Abstract: Learning to defer asks a predictive system when to act autonomously and when to defer to a human expert. Population-adaptive deferral extends this probl

tutorialsarxiv-cs-lg

21 Sept 2026

On-Demand Attention: Language Models Know When to Recall

arXiv:2609.20734v1 Announce Type: new Abstract: Reasoning and agentic workloads increasingly demand efficient long-context inference. Yet full-attention decoding reads the growing history at every ste

18 Sept 2026

Hardware

WFM: Wiki Foundation Model for Complex Agentic Reasoning

arXiv:2609.18182v1 Announce Type: new Abstract: Real-world agents fundamentally require persistent non-parametric knowledge for dynamic reasoning, i.e., long-term memory and retrieval-augmented genera

hardwarearxiv-cs-ai

17 Sept 2026

JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

arXiv:2609.17475v1 Announce Type: new Abstract: Capable open-weight models make local coding and reasoning attractive, but their context and execution state strain laptop memory. We present JustFit, a

local-aiarxiv-cs-ai

16 Sept 2026

Video-HolmesV2: Can MLLMs Reason with Spatio-Temporal Audio-Visual Evidence in Long Videos?

model-releasesarxiv-cs-cv

arXiv:2609.17248v1 Announce Type: new Abstract: Multimodal Large Language Models have demonstrated impressive video understanding, yet their ability to reason over long-form narratives is often masked

16 Sept 2026

BudgetBench: A Budget-Tiered Protocol and Pilot Harness for Memory Strategy Evaluation in Local Large Language Model Agents

arXiv:2609.13149v1 Announce Type: cross Abstract: For local large language model agents, active context is a scarce resource: memory capacity, prefill latency, cache growth, and service objectives all

Carryover Drafting: Recycling Rejected States for Speculative Decoding

arXiv:2609.14717v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by verifying multiple drafted tokens in parallel, allowing a single target forward pass to accept sever

Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection

arXiv:2412.03044v3 Announce Type: replace Abstract: Video anomaly detection (VAD) is a vital yet complex open-set task in computer vision, commonly tackled through reconstruction-based methods. Howeve

local-aiarxiv-cs-cv

Inoculation Midtraining with Learned Neologisms

arXiv:2609.15886v1 Announce Type: new Abstract: Large language models (LLMs) often learn both desirable and undesirable properties during post-training. We study whether midtraining, an earlier traini

safetyarxiv-cs-cl

Planning in the Backbone: DiffAdapterVLA for Native Continuous Trajectory Generation with Driving VLMs

arXiv:2609.15322v1 Announce Type: cross Abstract: Pretrained driving vision-language models (VLMs) integrate visual, route, language, and driving context into rich driving priors, yet their representa

ShopEase: A Generative AI-Based Multi-Agent Framework for Intelligent Enterprise Customer Support Using Hybrid Retrieval-Augmented Generation

arXiv:2609.13856v1 Announce Type: new Abstract: Enterprise customer support systems must answer customer questions correctly, retrieve the right policy information, use customer context, and pass diff

TTDF: A Two-Stage Framework for Reliable Surgical Phase Transition Detection

arXiv:2609.14624v1 Announce Type: new Abstract: Reliable workflow transition detection is important for context-aware surgical assistance and downstream decision support. However, online surgical phas

researcharxiv-cs-cv

Doc2FRC: Length-Consistent Document-Level Machine Translation via Fixed-Range Chunking

arXiv:2609.12674v1 Announce Type: new Abstract: Advanced large language models (LLMs) with long context windows can substantially reduce input truncation in document-level machine translation (DocMT).

safetyarxiv-cs-cl

14 Sept 2026

Demystifying the Privacy-Utility Trade-off in LLM Interactions

arXiv:2609.10992v1 Announce Type: new Abstract: The integration of Large Language Models into daily tasks relies on context-rich instructions, inevitably exposing sensitive user information. Current p

local-aiarxiv-cs-ai

12 Sept 2026

When Does Text Inform? Benchmarking Information-Theoretic Metrics for Multimodal Time-Series Forecasting

arXiv:2609.11282v1 Announce Type: new Abstract: Multimodal forecasting models that combine time series with text annotations promise richer prediction through textual context, but how do we know wheth

12 Sept 2026

A Voice-Interactive Multi-Agent System for Smart Operating Rooms: Architecture Design and Key Technologies

arXiv:2609.11231v1 Announce Type: cross Abstract: This paper presents SurgicalRoomAgent, a voice-interactive multi-agent system for smart operating rooms based on large language models (LLMs). The sys

PRAGMA: Evaluating Personalized Guidance with Memory Alignment in Lifelong Conversations

arXiv:2609.09664v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as personalized assistants that interact with users over extended periods of time. As conversatio

Smart Adaptive Computing Across the Continuum: LLMs in IoT-Edge-Cloud Resource Management

arXiv:2609.09348v1 Announce Type: cross Abstract: Managing resources across IoT, edge, and cloud layers calls for continuous, context-aware decisions under constraints that rarely stay fixed. Deep rei

agentsarxiv-cs-ai

SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations

arXiv:2609.11414v1 Announce Type: new Abstract: Large language models exhibit complementary strengths, motivating routing methods that dispatch each query to the most suitable model. Although existing

researcharxiv-cs-cl

Do LLMs Make More Mistakes If They Do Not Believe the Input Data?

arXiv:2609.09363v1 Announce Type: new Abstract: Large language models (LLMs) are prone to hallucinating or misinterpreting facts, which impairs their usability in retrieval-augmented generation or dat

local-aiarxiv-cs-cl

10 Sept 2026

EEGBind: Detecting Source-Level Interictal Epileptiform Discharges via EEG-Centric Multimodal Binding

arXiv:2609.09728v1 Announce Type: new Abstract: Source-level analysis of interictal epileptiform discharges (IEDs) is relevant to presurgical evaluation and treatment planning because it helps charact

10 Sept 2026

Adaptive Cost-Sensitive Machine Learning for Autonomous Robot Navigation Failure Prediction: When Not All Errors Are Equal

arXiv:2609.05593v1 Announce Type: new Abstract: Autonomous robot navigation failures differ not only in categorical severity but also in the physical context in which they occur. A near-miss at low sp

agentsarxiv-cs-ro

CAM: Question Answering on Entity-Centric Videos with Continuous Extraction and Adaptive Querying

arXiv:2609.06504v1 Announce Type: new Abstract: Memory facilitates question answering over long videos by extracting and retrieving facts to fit within the limited context windows of multimodal LLMs (

researcharxiv-cs-cv

CausalChapter: Improving Long-Video Chaptering with Interventional Dependency Modeling

arXiv:2609.08686v1 Announce Type: new Abstract: Long-form instructional videos require automatic chaptering to support browsing, navigation, and knowledge access. Recent long-context language models c

researcharxiv-cs-cv

Knowing When Not to Answer: Abstention and Refusal Reasoning in Vision--Language Models

arXiv:2609.05540v1 Announce Type: new Abstract: Many medical conditions require diagnosis through detailed, multi-context clinical assessment rather than from visual appearance alone. Despite this, vi

safetyarxiv-cs-cv

Unifying ICL, SFT, KL-Regularized RL Through a Bayesian Lens

arXiv:2609.05111v1 Announce Type: new Abstract: Large language models are now trained and evaluated under a diverse set of paradigms: supervised fine-tuning (SFT), few-shot in-context learning (ICL),

7 Sept 2026

BASP: Communication-Efficient Batch-Aware Sequence Parallelism for LLM Training

arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due t

Can LLMs Extract Architectural Design Decisions from Source Code Commits? - A Preliminary Exploratory Study

arXiv:2609.03721v1 Announce Type: cross Abstract: Context: Architectural Design Decisions (ADDs) capture the rationale behind the structure and evolution of software systems but are rarely documented

GrowPage: On-Demand KV Budgeting for Efficient LLM Reasoning Serving

arXiv:2609.03494v1 Announce Type: new Abstract: Long-output reasoning has made the key--value (KV) cache a critical memory bottleneck for efficient LLM serving. Existing KV compression methods usually

The Civilization Framework: Sovereign-Anchored Communication Between Personal Multi-Agent Systems

arXiv:2609.03425v1 Announce Type: cross Abstract: Humans are the transport layer between AI systems, losing context at every hop. We present the Civilization Framework, whose addressable party is the

agentsarxiv-cs-ai

The Geometry of Ignorance: LLMs Know When to Temper Bayesian Priors

arXiv:2609.02959v1 Announce Type: cross Abstract: What does a language model predict when it has few clues? The answer lurks in its unembedding geometry: a single direction of the unembedding matrix e

Why Gated DeltaNet Survives 4-Bit Quantization: NVFP4 W4A4 for the Recurrent Half of a Hybrid 27B LLM

arXiv:2609.04098v1 Announce Type: new Abstract: Hybrid LLMs pair softmax attention with linear-attention layers such as Gated DeltaNet (GDN), whose recurrent state summarizes the context in fixed size

local-aiarxiv-cs-ai

AdaMem: Learning What to Remember with Adaptive Memory Policies for Personalized Agents

arXiv:2606.21144v2 Announce Type: replace-cross Abstract: Long-term memory systems allow LLM agents to preserve information beyond a single context window, but most systems focus on storing and retrie