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Many healthcare organizations report that traditional worklist systems rely on rigid rules that ignore critical context, radiologist specialization, current workload, fatigue levels, and case complexi

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Model Releases

Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory

DGX agent

arXiv:2602.06025v2 Announce Type: replace Abstract: Memory is increasingly central to Large Language Model (LLM) agents operating beyond a single context window, yet most existing systems rely on offl

model-releasesarxiv-cs-cl

21 May 2026

Mem-pi: Adaptive Memory through Learning When and What to Generate

arXiv:2605.21463v1 Announce Type: new Abstract: We present Mem-pi, a framework for adaptive memory in large language model (LLM) agents, where useful guidance is generated on demand rather than retrie

agentsarxiv-cs-cl

Applications

Multi-Week, In-Class Deployments of Telepresence Robots With Four Homebound K-12 Students: Benefits, Challenges, and Recommendations

arXiv:2605.20431v1 Announce Type: cross Abstract: Missing significant amounts of school during K-12 education is known to put students' cognitive and social development at risk. Alternatives such as h

applicationsarxiv-cs-ro

Industry

new codex ships today!

new codex ships today! It’s Codex Thursday, and yes, we have updates for you. First up: Appshots, a new way to bring the context of what you’re working on into Codex. On your Mac, press Command-Comman

industrysam-altman--x

Nonlocal operator learning for fMRI encoding and decoding tasks

arXiv:2605.20389v1 Announce Type: new Abstract: Functional MRI data exhibit high-dimensional spatiotemporal structure, making both prediction and decoding challenging. In this work, we investigate neu

OCTOPUS: Optimized KV Cache for Transformers via Octahedral Parametrization Under optimal Squared error quantization

arXiv:2605.21226v1 Announce Type: new Abstract: The key-value (KV) cache dominates memory bandwidth and footprint in long-context autoregressive inference. Recent rotation-preconditioned codecs (Turbo

Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches

arXiv:2510.04905v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have significantly improved automated code generation. While existing approaches have achieved

agentsarxiv-cs-cl

RT @huntlovell: re: interpreters (since we''ve gotten asked this a few times) The proof will be in the evals/task-set for your agent, but…

This tweet by Hunt Lovell, shared by Harrison Chase, addresses questions about interpreters in the context of AI agent evaluation. It suggests that the effectiveness of interpreters should be validate

agentsharrison-chase--x

The Yes-Man Syndrome: Benchmarking Abstention in Embodied Robotic Agents

arXiv:2605.20544v1 Announce Type: cross Abstract: Vision-language models (VLMs) are used as high-level planners for embodied agents, translating natural language instructions and visual observations i

Versa applies zero-trust controls to AI agent actions with new MCP architecture

Secure access service edge firm Versa Networks Inc. today introduced a zero-trust architecture for the Model Context Protocol that validates every action an artificial intelligence agent takes inside

agentssiliconangle

VISTA: Technical Report for the Ego4D Short-Term Object Interaction Anticipation at EgoVis 2026

arXiv:2605.20901v1 Announce Type: new Abstract: We propose VISTA, a V-JEPA Integrated StillFast Temporal Anticipator for the Ego4D Short-Term Object Interaction Anticipation (STA) Challenge at EgoVis

Why Aggregate Accuracy is Inadequate for Evaluating Fairness in Law Enforcement Facial Recognition Systems

arXiv:2603.28675v2 Announce Type: replace Abstract: Facial recognition systems are increasingly deployed in law enforcement and security contexts, where algorithmic decisions can carry significant soc

safetyarxiv-cs-cv

Add a Specialized Deep Research Skill to Agent Harnesses

model-releasesnvidia-developer

This article covers the NVIDIA AI-Q Blueprint for building specialized deep research agents that empower AI systems to gather context, synthesize information, and support complex decision-making acros

Backtracking When It Strays: Mitigating Dual Exposure Biases in LLM Reasoning Distillation

arXiv:2605.19433v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success in complex reasoning tasks via long chain-of-thought (CoT), yet their immense computatio

Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation

arXiv:2605.19986v1 Announce Type: cross Abstract: Fine-grained manipulation marks a regime where global scene context no longer suffices, and success hinges on the tight coupling of local attribute gr

Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding

arXiv:2605.20104v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates large language model inference by leveraging a draft-then-verify paradigm. To maximize the acceptance rate, rece

local-aiarxiv-cs-ai

Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models

arXiv:2410.15362v2 Announce Type: replace-cross Abstract: Aligned Large Language Models (LLMs) have attracted significant attention for their safety, particularly in the context of jailbreak attacks t

I highly recommend this. The Agentic Review is a new podcast from @QodoAI hosted by Itamar Friedman and Nnenna Ndukwe, and it's a great AI c…

I highly recommend this. The Agentic Review is a new podcast from @QodoAI hosted by Itamar Friedman and Nnenna Ndukwe, and it's a great AI coding show that's neither hype nor doom. It's honest convers

agentsdair-ai--x

LLM-Based Financial Sentiment Analysis in Arabic: Evidence from Saudi Markets

arXiv:2605.19714v1 Announce Type: new Abstract: Investor sentiment shapes financial markets, yet modeling sentiment in Arabic financial contexts remains challenging due to linguistic complexity and li

researcharxiv-cs-cl

Hardware

OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond

arXiv:2605.19660v1 Announce Type: cross Abstract: The rapid advancement toward long-context reasoning and multi-modal intelligence has made the memory footprint of the Key-Value (KV) cache a dominant

hardwarearxiv-cs-cl

Hardware

PiKV: KV Cache Management System for Mixture of Experts

arXiv:2508.06526v3 Announce Type: replace-cross Abstract: As large-scale language models continue to scale up in both size and context length, the memory and communication cost of key-value (KV) cache

hardwarearxiv-cs-ai

RECIPE: Procedural Planning via Grounding in Instructional Video

arXiv:2605.19976v1 Announce Type: new Abstract: Visual planning asks a model to generate the remaining steps of a procedure in natural language given a partial video context and a goal. Progress on th

A semantic mutation metric for metamorphic relation adequacy in scientific computing programs

arXiv:2605.17437v1 Announce Type: cross Abstract: Context. Metamorphic Testing addresses the test-oracle problem in scientific computing, but classical Mutation Score operates on syntactic AST mutatio

ADR: An Agentic Detection System for Enterprise Agentic AI Security

arXiv:2605.17380v1 Announce Type: new Abstract: We present the Agentic AI Detection and Response (ADR) system, the first large-scale, production-proven enterprise framework for securing AI agents oper

Attend Locally, Remember Linearly: Linear Attention as Cross-Frame Memory for Autoregressive Video Diffusion

arXiv:2605.16579v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion is a powerful paradigm for streaming and interactive video generation. However, its reliance on softmax self-attenti

local-aiarxiv-cs-cv

Compounding Disadvantage: Auditing Intersectional Bias in LLM-Generated Explanations Across Indian and American STEM Education

model-releasesarxiv-cs-cl

arXiv:2601.14506v3 Announce Type: replace-cross Abstract: Large language models are increasingly deployed in STEM education for personalized instruction and feedback across institutions in high- and l

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective

arXiv:2605.18421v1 Announce Type: cross Abstract: Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution. However, memory is also essential for agen

Tutorials

Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation

arXiv:2605.16350v1 Announce Type: cross Abstract: We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules,

tutorialsarxiv-cs-ai

Global Automation Atlas

arXiv:2605.17086v1 Announce Type: cross Abstract: Automation affects the labour content of work differently across different contexts. Yet, most existing exposure measures assign fixed scores to tasks

researcharxiv-cs-ai

Herding CATs: ALARA for Agent Harness Engineering in Portable Composable Multi-Agent Teams

arXiv:2603.20380v2 Announce Type: replace-cross Abstract: Industry practitioners and academic researchers regularly use multi-agent systems to accelerate their work, but the applications through which

local-aiarxiv-cs-ai

I made a tool to use AgentRouter models in OpenCode

The search results focus on OpenCode + Ollama integration but don't specifically cover the AgentRouter tool. Let me provide a knowledge base entry based on what the title and context suggest: A tool d

local-air-ollama

Improving BM25 Code Retrieval Under Fixed Generic Tokenization: Adaptive q-Log Odds as a Drop-In BM25 Fix

arXiv:2605.18561v1 Announce Type: cross Abstract: In retrieval-augmented coding, failures often begin when the relevant file is absent from the retrieved context. Under frozen generic tokenization, wh

LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs

arXiv:2605.17260v1 Announce Type: new Abstract: The fundamental challenge in scaling Video Large Language Models (Video LLMs) to long-form video lies in managing the explosion of visual-token context

researcharxiv-cs-cv

Most human tasks are not Markovian, the optimal next action cannot be determined solely by looking at the current state. It depends heavily …

agentsfrancois-chollet--x

Most human tasks are not Markovian, the optimal next action cannot be determined solely by looking at the current state. It depends heavily on the past trajectory, the original intent, and context con

NOETHER: A Constructive Framework for Metamorphic Pattern Discovery from Operator Algebras

arXiv:2605.17390v1 Announce Type: cross Abstract: Context. Metamorphic Testing is recognised in IEEE/ISO software-testing standards and increasingly recommended for AI systems, but its progress is bot

Nuxt MCP Toolkit now supports MCP apps

The Nuxt MCP Toolkit has been updated to support MCP apps, expanding its capabilities for developers working with Nuxt and Model Context Protocol applications. This enhancement likely enables better i

agentsvercel-blog

Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry

arXiv:2605.16325v1 Announce Type: cross Abstract: Phase-transition phenomena in deep learning (grokking, emergent capabilities, and ontological reorganization under context shift) have been studied th

Prompt Compression in Diffusion Large Language Models: Evaluating LLMLingua-2 on LLaDA

arXiv:2605.17932v1 Announce Type: cross Abstract: Prompt compression reduces inference cost and context length in large language models, but prior evaluations focus primarily on autoregressive archite

Query-Conditioned Knowledge Alignment for Reliable Cross-System Medical Reasoning

arXiv:2605.18570v1 Announce Type: new Abstract: Cross-domain knowledge alignment is essential for integrating heterogeneous medical systems, yet existing approaches typically treat entity alignment as

REC-RL: Referring expression counting via Gaussian and range-based reward optimization

arXiv:2605.16460v1 Announce Type: new Abstract: Referring expression counting (REC) is an intention-driven task that requires context-aware visual reasoning. While recent vision-language models incorp

safetyarxiv-cs-cv

SocialMemBench: Are AI Memory Systems Ready for Social Group Settings?

arXiv:2605.17789v1 Announce Type: cross Abstract: Memory systems for AI assistants were built for single-user dialogue and fail characteristically when applied to multi-party social group settings. Th

Spatial Blindness in Whole-Slide Multiple Instance Learning

arXiv:2605.17449v1 Announce Type: cross Abstract: Whole-slide MIL models are often called context-aware once graphs, Transform ers, or state-space modules are placed above patch embeddings. We show th

researcharxiv-cs-ai

Speak Your Mind: The Speech Continuation Task as a Probe of Voice-Based Model Bias

arXiv:2509.22061v2 Announce Type: replace-cross Abstract: Speech Continuation (SC) is the task of generating a coherent extension of a spoken prompt while preserving both semantic context and speaker

safetyarxiv-cs-cl

TabH2O: A Unified Foundation Model for Tabular Prediction

model-releasesarxiv-cs-lg

arXiv:2605.18383v1 Announce Type: new Abstract: We present TabH2O, a foundation model for tabular data that performs classification and regression in a single forward pass via in-context learning. Tab

The Bayesian Geometry of Transformer Attention

arXiv:2512.22471v5 Announce Type: replace-cross Abstract: Transformers often appear to perform Bayesian reasoning in context, but verifying this rigorously has been impossible: natural data lack analy

The Loupe: A Plug-and-Play Attention Module for Amplifying Discriminative Features in Vision Transformers

arXiv:2508.16663v2 Announce Type: replace-cross Abstract: Fine-Grained Visual Classification (FGVC) requires models to focus on subtle, task-relevant regions rather than broad object context. We prese

researcharxiv-cs-ai

This is true of all agents, not just coding agents. Probably the biggest challenge that most companies run into in their agent strategy is g…

agentsfrancois-chollet--x

This is true of all agents, not just coding agents. Probably the biggest challenge that most companies run into in their agent strategy is getting agents the right constrained context to work with for