Search: “context”

Seeing Without Exposing: Adaptive Privacy Control for Open-World, Context-Hungry MLLMs

model-releasesarxiv-cs-cv

arXiv:2606.07175v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have raised new privacy challenges. On the data side, user-provided inputs often include unpredictable sensitiv

8 Jun 2026

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In-Context Multiple Instance Learning

DGX agent

arXiv:2606.06458v1 Announce Type: cross Abstract: Multiple Instance Learning (MIL) addresses problems where supervision is available at the level of bags of instances and has been successfully applied

applicationsarxiv-cs-cv

5 Jun 2026

In-Context Graphical Inference

arXiv:2606.05042v1 Announce Type: cross Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: exact algorithms are intractable for high-treewidth

safetyarxiv-cs-cl

4 Jun 2026

Instant-Fold: In-Context Imitation Learning for Deformable Object Manipulation

arXiv:2606.04269v1 Announce Type: cross Abstract: Deformable object manipulation (DOM) is challenging due to high-dimensional, partially observable states that evolve through long-horizon, topology-ch

4 Jun 2026

OpenRFM: Dissecting Relational In-Context Learning

arXiv:2606.04320v1 Announce Type: cross Abstract: Relational Foundation Models (RFMs) promise a single pre-trained predictor that, given any relational database, returns predictions in one forward pas

4 Jun 2026

Cross-Lingual Token Arbitrage: Optimizing Code Agent Context Windows via Local LLM Preprocessing

arXiv:2606.03618v1 Announce Type: new Abstract: AI-assisted coding agents are bottlenecked by input-token cost. Two pathologies of raw human input drive much of this overhead: tokenization inefficienc

Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction

arXiv:2510.15780v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is increasingly used to support renewable energy forecasting and grid operations. As renewable penetration grows,

local-aiarxiv-cs-lg

EntSQL: A Benchmark for Grounding Text-to-SQL in Long-Context Enterprise Knowledge

model-releasesarxiv-cs-cl

arXiv:2606.03363v1 Announce Type: new Abstract: Text-to-SQL enables natural language access to databases, and recent LLMs have substantially advanced its capabilities. Existing benchmarks such as Spid

Agents

MemTrain: Self-Supervised Context Memory Training

arXiv:2606.03197v1 Announce Type: new Abstract: Memory is an indispensable capability for long-horizon LLM agents, enabling them to preserve and utilize information accumulated across extended interac

agentsarxiv-cs-cl

A Lightweight Context-Driven Training-Free Network for Scene Text Segmentation and Recognition

arXiv:2503.15639v2 Announce Type: replace-cross Abstract: Modern scene text recognition systems often depend on large end-to-end architectures that require extensive training and are prohibitively exp

Context-aware child-directed speech detection from long-form recordings

arXiv:2606.01134v1 Announce Type: cross Abstract: Automatically distinguishing child-directed speech from adult-directed speech in long-form recordings is key to scalable analyses of children's langua

researcharxiv-cs-lg

Tutorials

Deep networks learn to parse uniform-depth context-free languages from local statistics

arXiv:2602.06065v3 Announce Type: replace-cross Abstract: Understanding how the structure of language can be learned from sentences alone is a central question in both cognitive science and machine le

tutorialsarxiv-cs-cl

Expanding Spatial and Temporal Context for Robotic Imitation Learning With Scene Graphs

arXiv:2606.01072v1 Announce Type: cross Abstract: Imitation learning enables robots to learn how to execute tasks via observation. However, real-world environments like homes and offices are often sev

safetyarxiv-cs-cv

Tutorials

Finding What Matters: Anchoring Context Knowledge with Evolving Indices for Iterative Retrieval

arXiv:2601.16462v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a dominant paradigm for mitigating hallucinations in Large Language Models (LLMs) by incorporating e

tutorialsarxiv-cs-cl

K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts

model-releasesarxiv-cs-cl

arXiv:2606.02404v1 Announce Type: new Abstract: Frontier model evaluations are shifting from foundational capabilities (e.g., instruction following and reasoning) toward compositional, agentic ones, b

Agents

Learning-To-Measure: In-Context Active Feature Acquisition

arXiv:2510.12624v2 Announce Type: replace-cross Abstract: Active feature acquisition (AFA) is a sequential decision-making problem where the goal is to improve model performance for test instances by

agentsarxiv-cs-ai

MomentKV: Closing the Directional Gap in KV Cache Eviction for Long-Context Inference

model-releasesarxiv-cs-lg

arXiv:2606.01563v1 Announce Type: new Abstract: Autoregressive decoding in Transformer-based language models relies on the KV cache, whose memory footprint grows linearly with sequence length and beco

Real2SAM2Real: Generative 3D Caches as Complementary Context for Video Diffusion

arXiv:2606.00299v1 Announce Type: cross Abstract: While Video Diffusion Models (VDMs) excel at synthesizing high-fidelity videos, enabling precise camera and scene control remains challenging. Existin

Tools

The end of fine-tuning: Why evals, context, and traces matter more

Fine-tuning isn't dead, but the way most teams iterate on AI products has split in two. A tiny fraction run continuous RL against their own environments; everyone else has moved the iteration loop out

toolsarize-ai

VICR: Visual In-Context Restoration for Real-World Image Super-Resolution

arXiv:2606.00704v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) requires balancing structural fidelity to degraded observations with realistic detail synthesis. However, e

local-aiarxiv-cs-cv

Why Do Time Series Models Need Long Context Windows?

arXiv:2606.01999v1 Announce Type: cross Abstract: Modern deep learning models for forecasting groups of time series rely on increasingly longer observation windows. However, the benefit of increasing

applicationsarxiv-cs-ai

A Novel Global Context-aware Deep Neural Network for Enhanced Brain Tumor Segmentation using Magnetic Resonance Images

arXiv:2605.30510v1 Announce Type: cross Abstract: Brain cancer's severity necessitates precise brain tumor segmentation, which is crucial for effective brain tumor diagnosis. Manual identification, bu

From Evidence to Design: Developing an AI-Augmented UX Research Point of View for Digital Wellbeing in Emergency and Public Safety Contexts

arXiv:2605.31146v1 Announce Type: cross Abstract: This paper investigates how User Experience Research (UXR) methods can be combined with AI-supported analysis to develop clearer design direction for

Tutorials

Personalize Your Large Vision-language Models With In-context Prompt Tuning

arXiv:2605.31513v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have demonstrated strong general multimodal capability and are increasingly deployed in downstream systems. This tr

tutorialsarxiv-cs-cv

Agents

PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers

arXiv:2506.14842v2 Announce Type: replace-cross Abstract: Building image classification models remains cumbersome in data-scarce domains, where collecting large labeled datasets is impractical. In-con

agentsarxiv-cs-ai

Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding

arXiv:2602.06161v2 Announce Type: replace-cross Abstract: Parallel diffusion decoding can accelerate diffusion language model inference by unmasking multiple tokens per step, but aggressive parallelis

Empathic Prompting: Non-Verbal Context Integration for Multimodal LLM Conversations

arXiv:2510.20743v2 Announce Type: replace-cross Abstract: We present Empathic Prompting, a novel framework for multimodal human-AI interaction that enriches Large Language Model (LLM) conversations wi

29 May 2026

Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy

arXiv:2509.21190v4 Announce Type: replace-cross Abstract: Time series anomaly detection (TSAD) is a critical task, but developing models that generalize to unseen data in a zero-shot manner remains a

29 May 2026

Benchmarking AI for low-resource contexts: Thinking beyond leaderboards

arXiv:2605.28508v1 Announce Type: new Abstract: Existing AI evaluation practices often fail to capture how systems actually perform in low-resource environments, where operational constraints shape us

COTTA: Context-Aware Transfer Adaptation for Trajectory Prediction in Autonomous Driving

arXiv:2604.00402v2 Announce Type: replace-cross Abstract: Developing robust models to accurately predict the trajectories of surrounding agents is fundamental to autonomous driving safety. However, mo

Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models

arXiv:2510.17620v2 Announce Type: replace Abstract: Large language models may encode sensitive information or outdated knowledge that needs to be removed, to ensure responsible and compliant model res

researcharxiv-cs-cl

HGMEM: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modeling

arXiv:2512.23959v3 Announce Type: replace-cross Abstract: Multi-step retrieval-augmented generation (RAG) has become a widely adopted strategy for enhancing large language models (LLMs) on tasks that

MIRAGE: Context-Aware Prompt Injection against Mobile GUI Agents via User-Generated Content

arXiv:2605.28116v1 Announce Type: cross Abstract: Mobile graphical user interface (GUI) agents driven by vision-language models (VLMs) perceive the screen as rendered pixels and choose actions from wh

Starburst bets on semantic context to solve enterprise AI trust problem

Starburst Data Inc. today is expanding its push into enterprise artificial intelligence with the introduction of a platform aimed at allowing organizations to run AI workloads directly on distributed

applicationssiliconangle

VideoCanvas: Unified Video Completion from Arbitrary Spatiotemporal Patches via In-Context Conditioning

model-releasesarxiv-cs-cv

arXiv:2510.08555v2 Announce Type: replace Abstract: Existing controllable video generation methods are typically designed for rigid, task-specific settings, such as first-frame image-to-video, inpaint

VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization

arXiv:2511.11896v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently shown strong potential in vulnerability detection (VD). However, accurately detecting vulnerabiliti

Whose Is This?: Context-Aware Object Ownership Inference with Uncertainty-Guided Questioning

arXiv:2605.28087v1 Announce Type: new Abstract: Service robots must infer object ownership to correctly interpret instructions such as 'bring me my cup.' However, ownership is a latent attribute that

researcharxiv-cs-ro

AI evaluation may bias perceptions: The importance of context in interpreting academic writing

arXiv:2605.26662v1 Announce Type: cross Abstract: This paper examines how estimates of AI use in scientific writing can be biased when evaluation methods ignore contextual differences across countries

Bounded Path Context: A Controlled Study of Visible Path History in LLM-Based Knowledge Graph Question Answering

arXiv:2605.26645v1 Announce Type: new Abstract: LLM-based knowledge-graph question answering (KGQA) delegates graph traversal to language models, turning each question into a sequence of local relatio

local-aiarxiv-cs-cl

ContextGuard: Structured Self-Auditing for Context Learning in Language Models

arXiv:2605.26827v1 Announce Type: cross Abstract: Recent benchmarks reveal that despite strong reasoning capabilities, large language models (LLMs) still struggle to faithfully apply complex contextua

MicroSpec: Accelerating Speculative Decoding with Lightweight In-Context Vocabularies

arXiv:2605.26444v1 Announce Type: new Abstract: Large language models typically employ vocabularies of over 100k tokens, which creates a major computational bottleneck at the final linear projection l

local-aiarxiv-cs-cl

MEMOR-E: In-Context and Fine-Tuned LLM Personalization for Alzheimer's Assistive Robotics

arXiv:2605.23941v1 Announce Type: new Abstract: Alzheimer's disease is a neurodegenerative disorder marked by progressive declines in memory and language that reduce independence in daily life, motiva

26 May 2026

Polynomial Context-Truncation Sensitivity in Autoregressive Language Models: Sequential Wyner-Ziv Bounds for KV Cache Compression

arXiv:2605.25085v1 Announce Type: cross Abstract: We study the rate-distortion limits of online KV cache compression in autoregressive language models, formulating it as sequential Wyner-Ziv source co

26 May 2026

Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking

arXiv:2605.23118v1 Announce Type: cross Abstract: Tracking tumor lesions across serial CT scans is essential for oncological response assessment. Existing automated methods face a fundamental trade-of

25 May 2026

RAS: Reflection-Augmented Scaling with In-Context Learning for Executable Cypher Query Generation

arXiv:2605.22937v1 Announce Type: new Abstract: Inference-time scaling can reduce errors in structured query generation, but methods to allocate the compute for query code generation remains underexpl

researcharxiv-cs-cl

25 May 2026

Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts

arXiv:2605.23597v1 Announce Type: new Abstract: Matching person names across heterogeneous records is a core challenge in entity resolution, especially within linguistically and culturally complex env

applicationsarxiv-cs-cl

25 May 2026

Break the context window barrier with Amazon Bedrock AgentCore

model-releasesaws-ml-blog

In this post, you will learn how to implement Recursive Language Models (RLM) using Amazon Bedrock AgentCore Code Interpreter and the Strands Agents SDK. By the end, you will know how to process docum

21 May 2026

Agentmw: Open-source middleware for AI agents — catches mid-run failures,compresses stale context, and grows a reasoning library across runs. Any model, any framework.