Search: “context”

SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition

arXiv:2606.03610v1 Announce Type: new Abstract: Skeleton-based action recognition aims to understand human behaviors from body joint sequences and is especially challenging in the one-shot setting, wh

safetyarxiv-cs-cv

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Research

Social Caption: Evaluating Social Understanding in Multimodal Models

DGX agent

arXiv:2601.14569v2 Announce Type: replace Abstract: Social understanding abilities are crucial for multimodal large language models (MLLMs) to interpret human social interactions. We introduce SOCIAL

researcharxiv-cs-cl

3 Jun 2026

Applications

Solipsistic Superintelligence is Unlikely to be Cooperative

arXiv:2606.03237v1 Announce Type: new Abstract: AI's central challenge is shifting from capability to coexistence. The dominant paradigm in AI research focuses on developing powerful agents that treat

applicationsarxiv-cs-ai

Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning

arXiv:2606.02842v1 Announce Type: new Abstract: Multimodal spatial reasoning often relies on long chains of intermediate textual and visual thoughts, where accumulating visual tokens and dense cross-m

researcharxiv-cs-lg

SplitAdapter: Load-Aware Humanoid Loco-Manipulation via Factorized Adaptation

arXiv:2606.03297v1 Announce Type: new Abstract: Humanoid loco-manipulation requires stable whole-body control under varying object masses and pickup/placement heights. This becomes particularly challe

safetyarxiv-cs-ro

Staying Alive: Uncensored Survival Analysis with Tabular Foundation Models

arXiv:2606.03689v1 Announce Type: cross Abstract: Survival Analysis (SA) is a statistical framework that models the time span until some event of interest occurs. Widely used in several domains, inclu

Synthesize and Reward -- Reinforcement Learning for Multi-Step Tool Use in Live Environments

arXiv:2606.03892v1 Announce Type: cross Abstract: Training LLMs to orchestrate multi-step tool calls is held back by three coupled obstacles: realistic stateful execution environments are costly to bu

Test-Time Optimization of Physical Query Plans with LLMs

arXiv:2602.10387v2 Announce Type: replace-cross Abstract: Traditional query optimization relies on cost-based optimizers that estimate execution cost (e.g., runtime, memory, and I/O) using predefined

TGV-KV: Text-Grounded KV Eviction for Vision-Language Models

arXiv:2606.03075v1 Announce Type: new Abstract: Vision-Language Models (VLMs) inherit the auto-regressive generation paradigm and cache the keys and values (KV) of all previous tokens to accelerate in

safetyarxiv-cs-cv

The Agent's First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios

arXiv:2601.08173v2 Announce Type: replace Abstract: The rapid evolution of Multi-modal Large Language Models (MLLMs) has advanced workflow automation; however, existing research mainly targets perform

Tutorials

the best agents aren't just built with the best models: they're built with harnesses purpose-built for the task at hand here's a guide on ho…

tutorialsharrison-chase--x

the best agents aren't just built with the best models: they're built with harnesses purpose-built for the task at hand here's a guide on how to build a harness that's really good at feeding the model

The Deliberative Illusion: Diagnosing Factual Attrition and Stance Homogenization in Multi-Agent LLM Deliberation

arXiv:2606.03032v1 Announce Type: new Abstract: Multi-agent LLM systems often treat consensus as evidence of successful interaction. For deliberative problems, however, reliability depends on whether

agentsarxiv-cs-cl

The Impact of Configuring Agentic AI Coding Tools on Build-vs-Buy Decisions: A Study Protocol

arXiv:2606.03907v1 Announce Type: cross Abstract: Agentic AI coding tools write code with increasing autonomy and in doing so decide when to import a library and when to implement functionality from s

This SkillOpt paper from Microsoft is a must-read! (bookmark it) I was a bit skeptical of the results reported in the paper when I shared it…

This SkillOpt paper from Microsoft is a must-read! (bookmark it) I was a bit skeptical of the results reported in the paper when I shared it a few days ago. However, I managed to integrate it into my

agentsdair-ai--x

ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents

arXiv:2606.03054v1 Announce Type: new Abstract: Tool-augmented vision-language agents can acquire external perceptual evidence through OCR, detection, segmentation, and other tools, but executing ever

Towards Non-Monotonic Entailment in Propositional Defeasible Standpoint Logic

arXiv:2606.03655v1 Announce Type: new Abstract: Recent work in defeasible reasoning has seen notions of preferential semantics and entailment in the style of Kraus et al. applied to modal logics. Howe

TreeFlash: Parallel AR-Approximation for Faster Speculative Decoding

arXiv:2606.03819v1 Announce Type: new Abstract: One-shot block drafters for speculative decoding generate the full draft in a single forward pass, achieving strong throughput by eliminating sequential

researcharxiv-cs-lg

VLESA: Vision-Language Embodied Safety Agent for Human Activity Monitoring

model-releasesarxiv-cs-cv

arXiv:2606.03954v1 Announce Type: new Abstract: As AI systems increasingly assist humans in physical tasks, ensuring safety becomes paramount -- physical actions carry immediate and irreversible conse

vLLM Semantic Router: Signal Driven Decision Routing for Mixture-of-Modality Models

arXiv:2603.04444v3 Announce Type: replace-cross Abstract: As large language models (LLMs) diversify across modalities, capabilities, and cost profiles, the problem of intelligent request routing -- se

Local Ai

VulnAgent-R2: Evidence-Calibrated Multi-Agent Auditing for Repository-Level Vulnerability Detection

arXiv:2603.13384v2 Announce Type: replace-cross Abstract: Software vulnerabilities often depend on cross-file data flow, build options, framework conventions, and runtime guards, so isolated function

local-aiarxiv-cs-ai

World Models Meet Language Models: On the Complementarity of Concrete and Abstract Reasoning

arXiv:2606.03603v1 Announce Type: cross Abstract: World models and multimodal large language models (MLLMs) provide complementary capabilities for predicting future outcomes from static visual observa

safetyarxiv-cs-cl

A Communication-Centric 6G-LLM Architecture for Scalable Tactical Autonomous Defense Vehicle Networks

arXiv:2606.01312v1 Announce Type: cross Abstract: The integration of Artificial Intelligence (AI) and emerging 6G networks introduces new opportunities for scalable coordination in tactical autonomous

A Machine-to-Machine Knowledge-Guided LLM Agent for Generalizable Radiotherapy Treatment Planning

model-releasesarxiv-cs-ro

arXiv:2606.00922v1 Announce Type: cross Abstract: In this work, we propose a prototype machine-to-machine (M2M) knowledge-guided Large Language Model (LLM) framework for automated radiotherapy treatme

A Modelling and Evaluation Framework for EuroCrops-Driven Sentinel-2 Crop Segmentation

arXiv:2606.00676v1 Announce Type: new Abstract: This work presents a configurable pipeline for generating semantic-segmentation-ready agricultural datasets from Sentinel-2 imagery and EuroCrops parcel

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A Novel Data Augmentation Strategy for Robust Deep Learning Classification of Biomedical Time-Series Data: Application to ECG and EEG Analysis

arXiv:2507.12645v1 Announce Type: cross Abstract: The increasing need for accurate and unified analysis of diverse biological signals, such as ECG and EEG, is paramount for comprehensive patient asses

AdaCodec: A Predictive Visual Code for Video MLLMs

arXiv:2606.02569v1 Announce Type: cross Abstract: Video is temporally redundant: adjacent frames usually share most objects, background, and layout. Yet existing video multimodal large language models

Tutorials

AdaptiveK: Complexity-Driven Sparse Autoencoders for Interpretable Language Model Representations

arXiv:2508.17320v3 Announce Type: replace Abstract: Understanding the internal representations of large language models (LLMs) remains a central challenge for interpretability research. Sparse autoenc

tutorialsarxiv-cs-lg

Agent Operating Systems (AOS): Integrating Agentic Control Planes into, and Beyond, Traditional Operating Systems

arXiv:2606.01508v1 Announce Type: cross Abstract: Traditional operating systems were designed around deterministic programs, explicit control flow, and human initiated workflows. Their core abstractio

AGENTCL: Toward Rigorous Evaluation of Continual Learning in Language Agents

arXiv:2606.02461v1 Announce Type: new Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future e

Agentic Authoring of Interactive Multiview Visualizations in Genomics

arXiv:2606.00370v1 Announce Type: cross Abstract: Diverse genomics data, scientific questions, and analysis tasks typically demand highly specialized visualizations. Therefore, users often must custom

Agentic Transformers Provably Learn to Search via Reinforcement Learning

arXiv:2606.00183v1 Announce Type: cross Abstract: Tree search is a central abstraction behind many language-agent reasoning and decision-making tasks: agents must explore actions, remember failures, a

Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimization

arXiv:2606.00008v1 Announce Type: new Abstract: Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives, where early design decisions strongly const

AI From the Margins (AIM): Rethinking Participatory AI Design Through the Lived Experience of Minoritized Communities

arXiv:2606.01171v1 Announce Type: cross Abstract: Artificial intelligence (AI) can reproduce and amplify the structural inequities faced by minoritized communities. Participatory AI has been proposed

Industry

AI in Defense: How Artificial Intelligence Is Reshaping National Security

This article explores the applications and impact of artificial intelligence on national security and defense operations, examining how AI technologies are transforming military capabilities, threat d

industrydatabricks

AI-IoT-Robotics Integration: Survey of Frameworks, Emerging Trends, and the Path Toward Connected Robotics

arXiv:2606.01015v1 Announce Type: cross Abstract: The convergence of Artificial Intelligence, the Internet of Things, and Robotics is no longer a futuristic vision; it is rapidly becoming the foundati

AMP: A Vendor-Neutral Wire Format for Agent Memory Operations

arXiv:2606.01138v1 Announce Type: cross Abstract: Agent-memory frameworks - mem0, Letta/MemGPT, Cognee, Zep/Graphiti, MemoryOS, MemTensor - each ship their own SDK, storage layout, and operational voc

ANDES: Agent Native Data Evolving Synthesis Tool for Autonomous Instruction Alignment

arXiv:2606.01279v1 Announce Type: new Abstract: AI agents are increasingly being tasked with automating AI research itself, particularly the critical post-training phase that transforms base LLMs into

ASKD-Whisper: Adaptive Self-knowledge Distillation for Efficient and Low-Latency Automatic Speech Recognition

arXiv:2601.19919v2 Announce Type: replace-cross Abstract: Knowledge distillation (KD) is one of the most effective paradigms for compressing large-scale foundation models into deployable architectures

Assessment of Generative Named Entity Recognition in the Era of Large Language Models

arXiv:2601.17898v2 Announce Type: replace Abstract: Named entity recognition (NER) is evolving from a sequence labeling task into a generative paradigm with the rise of large language models (LLMs). W

Automated Erythrocyte Detection and Tracking for Retinal Blood Flow Quantification in Erythrocyte-Mediated Angiography

arXiv:2606.01006v1 Announce Type: new Abstract: Capillary-level retinal blood flow (RBF) has strong potential as a biomarker for various ocular diseases. However, modalities for measuring capillary-le

researcharxiv-cs-cv

Automated Essay Scoring and Language Certification: Assessing Generalizability, Agreement and Validity for French

arXiv:2606.02009v1 Announce Type: new Abstract: In Automated Essay Scoring (AES), benchmarking practices have fostered minimalist evaluation practices, in contrast with the broader-view recommendation

safetyarxiv-cs-cl

Balancing Accuracy and Efficiency: Adaptive Dynamics Orchestration for Model Predictive Control

arXiv:2606.00085v1 Announce Type: new Abstract: Model Predictive Control (MPC) for autonomous navigation faces a fundamental trade-off between model accuracy and real-time efficiency. High-fidelity dy

safetyarxiv-cs-ro

Benchmarking Large Language Models for Cryptanalysis and Side-Channel Vulnerabilities

arXiv:2505.24621v3 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have transformed natural language understanding and generation, leading to extensive benchmarkin

Benchmarking LLM-as-a-Judge for Long-Form Output Evaluation

arXiv:2606.01629v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly used for long-form generation, reliably evaluating long-form outputs has become a critical challenge. L

Benchmarking Local LLMs for Natural-Language-to-SQL Querying in Biopharmaceutical Manufacturing: An Empirical Benchmark on Consumer-Grade Hardware

arXiv:2606.01338v1 Announce Type: new Abstract: Biopharmaceutical manufacturing organizations operate under regulatory frameworks such as FDA guidance, EU Good Manufacturing Practice (GMP), and the EU

Beyond Categories of Caste: Examining Caste Bias and Morality in Text-to-Image AI Models

arXiv:2606.00039v1 Announce Type: cross Abstract: Text-to-Image (T2I) models have shown promising utility across various domains. However, such models are also amplifying harmful societal biases in th

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization

arXiv:2505.18113v2 Announce Type: replace Abstract: Training quantized neural networks requires addressing the non-differentiable and discrete nature of the underlying optimization problem. To tackle

researcharxiv-cs-lg

Beyond One-shot: AI Agents for Learning in Field Experiments

arXiv:2606.02458v1 Announce Type: new Abstract: Organizations routinely run experiments for A/B testing, yet the data generated from one experiment is underutilized to inform subsequent intervention d