Search: “context”

Where's the Structure? A Systematic Literature Review of Empirical Research on Human-AI Collaboration and Hybrid Intelligence for Learning

arXiv:2606.05222v1 Announce Type: cross Abstract: Artificial intelligence (AI) has been applied across educational contexts to support learning. One approach to such support is 'human-AI collaboration

6 Jun 2026

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Agents

Personal AI Agent for Camera Roll VQA

DGX agent

arXiv:2606.05275v1 Announce Type: new Abstract: We study the personal camera roll visual question answering setting. In this setting, a conversational AI assistant can access a user's personal camera

agentsarxiv-cs-cv

5 Jun 2026

ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Models

arXiv:2601.02880v2 Announce Type: replace-cross Abstract: Every existing inference-time reasoning framework discards all failure context at problem boundaries, leaving a model solving problem 500 no w

5 Jun 2026

Trajectory Dynamics in Language Model Hidden States Predict Human Processing Costs Beyond Surprisal

arXiv:2606.05346v1 Announce Type: new Abstract: Human language comprehension unfolds sequentially: each word is processed in the context of those that came before, and the interpretation builds increm

local-aiarxiv-cs-cl

5 Jun 2026

Hardware

Cartridges at Scale: Training Modular KV Caches over Large Document Collections

arXiv:2606.04557v1 Announce Type: new Abstract: Large Language Models can reason over long contexts, yet prefilling millions of tokens is wasteful as much of the content remains static across queries.

hardwarearxiv-cs-cl

4 Jun 2026

Entropy Gate: Entropy Quenching for Near-Lossless Token Compression in LLM Pipelines

arXiv:2606.03739v1 Announce Type: new Abstract: LLM pipelines waste substantial token budgets on low-information content: repeated context, verbose responses, and redundant boilerplate. We introduce E

agentsarxiv-cs-cl

IdiomX A Multilingual Benchmark for Idiom Understanding, Retrieval, and Interpretation

arXiv:2606.02584v1 Announce Type: cross Abstract: Idiomatic expressions remain a persistent challenge for natural language processing because their meanings are often non-compositional, context-depend

Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding

arXiv:2606.03080v1 Announce Type: cross Abstract: Causal language models factorize sequence probabilities using only preceding context, leaving future information unexploited during training despite i

local-aiarxiv-cs-ai

Startup discovery platform @harmonic_ai rebuilt Scout, their AI platform using Deep Agents and LangSmith. Deep Agents: One frontier model + …

model-releasesharrison-chase--x

Startup discovery platform @harmonic_ai rebuilt Scout, their AI platform using Deep Agents and LangSmith. Deep Agents: One frontier model + two tool sets (global company data and firm-specific context

BOUTEF: A Multilingual Corpus for FakeNews in North Africa -- Language as a Weapon

arXiv:2606.00193v1 Announce Type: new Abstract: The rapid spread of fake news on social media has become a major challenge, particularly in multilingual and under-resourced contexts such as North Afri

Hardware

BudgetDraft: Acceptance-Aware Multi-View Training for Sparse-KV Speculative Decoding

arXiv:2606.00144v1 Announce Type: cross Abstract: Speculative decoding speeds up autoregressive decoding by using a drafter to propose multiple tokens that a verifier validates in parallel. In resourc

hardwarearxiv-cs-ai

Multimodal Function Vectors for Visual Relations

arXiv:2510.02528v2 Announce Type: replace Abstract: Large Multimodal Models (LMMs) demonstrate impressive in-context learning abilities from few multimodal demonstrations, yet the internal mechanisms

local-aiarxiv-cs-ai

OCC-RAG: Optimal Cognitive Core for Faithful Question Answering

arXiv:2606.00683v1 Announce Type: new Abstract: Recent progress in the development of language models has been defined by scale, with each generation absorbing more of the world's knowledge into its w

PMC-InterCPT: Rethinking Biomedical Interleaved Data for Multimodal Continued Pretraining

arXiv:2606.01049v1 Announce Type: new Abstract: Large-scale biomedical image-text datasets extracted from scientific literature provide valuable resources for medical multimodal model training. These

When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding

arXiv:2606.00953v1 Announce Type: new Abstract: Multi-agent Large Language Model (LLM) systems offer a way to decompose complex tasks, such as coding, through parallelization and context isolation. Ho

Eywa: Provenance-Grounded Long-Term Memory for AI Agents

model-releasesarxiv-cs-cl

arXiv:2605.30771v1 Announce Type: new Abstract: AI agents that persist across sessions need memory they can retrieve, audit, update, and erase. Existing memory systems often collapse source evidence,

1 Jun 2026

Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk

arXiv:2605.29788v1 Announce Type: new Abstract: Critical sequential decisions are rarely single-timescale: a strategic decision causally shapes the context in which every subsequent tactical choice is

safetyarxiv-cs-ai

Cloud CISO Perspectives: How to build an AI-ready security program for the public sector

model-releasesgoogle-cloud-ai

Welcome to the second Cloud CISO Perspectives for May 2026. Today, Usman Chaudhary, Field CISO, Google Public Sector, offers a guide for CISOs protecting government agencies and critical infrastructur

LogDx-CI: Benchmarking Log Reduction Tools for LLM Root-Cause Diagnosis

arXiv:2605.28876v1 Announce Type: cross Abstract: CI failure logs are large (median 5k lines, max 200k in this corpus) and noisy. Coding agents that try to debug them depend on an upstream tool to red

Native Audio-Visual Alignment for Generation

arXiv:2605.30073v1 Announce Type: new Abstract: Joint audio-video generation aims to synthesize temporally synchronized and semantically coherent visual-acoustic content. However, existing open-source

safetyarxiv-cs-cv

NICE: A Theory-Grounded Diagnostic Benchmark for Social Intelligence of LLMs

arXiv:2605.29685v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly applied in social contexts such as emotional companionship and customer service, measuring their social

Applications

Persona Conditioning of Brand Recommendations in Retrieval-Augmented Commercial Chat: A Prominence-Stratified Cross-Provider Audit

arXiv:2605.30207v1 Announce Type: new Abstract: The same prompt -- 'best CRM software' -- reaches AI assistants from buyers in widely different contexts: a solo founder, an enterprise VP, a UK SMB own

applicationsarxiv-cs-ai

Rethinking Post-Training Recipes for Multimodal Time-Series Forecasting

arXiv:2605.29401v1 Announce Type: new Abstract: Time-Series Foundation Models (TSFMs) excel at zero-shot unimodal forecasting using numerical data, but unlike LLMs they cannot consume multimodal, non-

Semantic and Visual Evidence for Efficient Long-Video Reasoning: A Solution for the HD-EPIC VQA Challenge

arXiv:2605.29402v1 Announce Type: cross Abstract: Understanding long-form egocentric videos remains challenging for multimodal large language models (MLLMs) due to limited context length and insuffici

Temporal Stability and Few-Shot Prompting in Math Task Assessment

arXiv:2605.30151v1 Announce Type: new Abstract: As AI tools become increasingly integrated into educational contexts, questions arise about both their stability over time and their responsiveness to p

Agentic Literacy Debt: A Structural Problem the AI Literacy Field Has Not Yet Named

arXiv:2605.27396v1 Announce Type: cross Abstract: Autonomous AI agents now plan, decide, and act on behalf of users across healthcare, financial services, and workplace contexts, often without step-by

Asking Is Not Enough: Protocol Sensitivity in LLM Confidence Calibration

arXiv:2605.27752v1 Announce Type: new Abstract: LLM confidence calibration is often evaluated by comparing two signals: token-probability scores and verbalized confidence. These signals are sometimes

Do Clinical Models Change Treatment Decisions?

arXiv:2605.28129v1 Announce Type: new Abstract: Clinical foundation models are evaluated with factual or exam-style medical QA, but treatment decisions must change when patient context changes. We int

Explaining is Harder Than Predicting Alone: Evaluating Concept-based Explanations of MLLMs as ICL Visual Classifiers

arXiv:2605.28215v1 Announce Type: new Abstract: In-context learning (ICL) enables multimodal large language models (MLLMs) to classify images from a few labelled examples. Yet, how these models use th

I'm proud to share that @Glean has surpassed 300M ARR, just five months after crossing 200M and growing ~3x over the past 15 months. This …

model-releasessonya-huang--x

I'm proud to share that @Glean has surpassed 300M ARR, just five months after crossing 200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about wh

MemGuard: Preventing Memory Contamination in Long-Term Memory-Augmented Large Language Models

arXiv:2605.28009v1 Announce Type: cross Abstract: Memory-augmented large language models extend reasoning beyond a fixed context window by maintaining long-term memory across interactions. However, ex

MeniOmni: A Structured Multimodal Benchmark for Holistic Meniscus Injury Assessment

model-releasesarxiv-cs-cv

arXiv:2605.28161v1 Announce Type: new Abstract: Clinical diagnosis of meniscus injuries requires radiologists to integrate volumetric MRI evidence with patient context (e.g., sex, age, BMI) and to pro

MGRetrieval: Memory-Guided Reflective Retrieval for Long-Term Dialogue Agents

arXiv:2605.27437v1 Announce Type: cross Abstract: Large Language Models (LLMs) have made significant progress in dialogue, yet redundant memory contexts severely limit their effectiveness in long-term

Reflective Dialogue between Teacher and Solver Agents for Video Question Answering

model-releasesarxiv-cs-cv

arXiv:2605.27885v1 Announce Type: new Abstract: Various approaches have been proposed to adapt Vision-Language Models (VLMs) to specialized domains for Video Question Answering, including fine-tuning

UNIQUE: Universal Top-k Sparse Attention for Training-free Inference and Sparsity-aware Training

arXiv:2605.27740v1 Announce Type: new Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the linear growth of the self-attention key-value (KV) cache. Top-k sparse att

FAB-Bench: A Framework for Adaptive RAG Benchmarking in Semiconductor Manufacturing

model-releasesarxiv-cs-cl

arXiv:2605.26476v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become critical for knowledge-intensive applications, yet evaluating its performance in vertical domains remain

Real Images, Worse Judgments: Evaluating Vision-Language Models on Concreteness and Imagery

arXiv:2605.27315v1 Announce Type: new Abstract: Visual inputs are often assumed to improve language understanding in multimodal models. We examine this assumption by asking whether vision-language mod

safetyarxiv-cs-cl

The Compressive Knowledge Graph Hypothesis: Which Graph Facts Matter for Scientific Hypothesis Generation?

arXiv:2605.27176v1 Announce Type: new Abstract: Knowledge graphs (KGs) can provide structured scientific context to language models, but it remains unclear which graph facts actually shape the generat

The MiniMax M2 series was one of the most widely used open-weight LLM series earlier this year. Now, we got a technical report with some int…

model-releasessebastian-raschka--x

The MiniMax M2 series was one of the most widely used open-weight LLM series earlier this year. Now, we got a technical report with some interesting tidbits. I summarized some of them below: 1. Full a

CyberMaskQA: A Privacy-Aware Benchmark for Evaluating Large Language Models in Cybersecurity Question Answering

arXiv:2605.24765v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly applied to cybersecurity question answering (QA) for critical tasks such as incident response and vulner

HumanFlow -- Diffusion-Driven MAV Navigation Among Humans via Tightly-Coupled Motion Tracking, Forecasting, and Control

arXiv:2605.25685v1 Announce Type: new Abstract: Robust and accurate perception of humans in their 3D scene context is essential for integrating robots into everyday environments. Existing approaches,

safetyarxiv-cs-ro

LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots

arXiv:2605.24417v1 Announce Type: new Abstract: Supervised classification for tabular data remains a core machine learning task, yet its reliance on large labeled datasets limits applicability in data

MedBeads: An Agent-Native, Immutable Data Substrate for Trustworthy Medical AI

arXiv:2602.01086v2 Announce Type: replace Abstract: Background: As of 2026, Large Language Models (LLMs) demonstrate expert-level medical knowledge. However, deploying them as autonomous 'Clinical Age

MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing

arXiv:2605.23986v1 Announce Type: cross Abstract: Memory is a fundamental component for enabling long-context LLM agents, supporting persistent state across interactions through a continuous serve-and

More Skills, Worse Agents? Skill Shadowing Degrades Performance When Expanding Skill Libraries

arXiv:2605.24050v1 Announce Type: cross Abstract: Skill libraries allow LLM agents to load task-specific instructions on demand, letting non-expert users solve domain-specific tasks through natural la

Personalize-then-Store: Benchmarking and Learning Personalized Memory for Long-horizon Agents

arXiv:2605.25535v1 Announce Type: new Abstract: Existing large language model (LLM) based memory systems apply universal, static policies that overlook a fundamental reality: the contexts that are wor

The Model Is Not the Product: A Dual-Pillar Architecture for Local-First Psychological Coaching

arXiv:2605.24411v1 Announce Type: new Abstract: Existing language model applications struggle to meet the demand for emotionally oriented support, primarily due to their inability to maintain deep, pe

PathNavigate: A Training-Free Pathology Agent with Surprise-Guided Scan and Shared Slide Memory for Whole-Slide Image VQA