Search: “agents”

SPECTRA: Pushing the KV Cache Beyond the 2-Bit Cliff via Spectral Transform Coding

model-releasesarxiv-cs-lg

arXiv:2608.07915v1 Announce Type: new Abstract: Large language models (LLMs) increasingly read long inputs in the agentic era, from whole documents and codebases to conversations across many turns. Th

11 Aug 2026

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

VTO: Visual Tool Orchestration for Video Anomaly Detection

DGX agent

arXiv:2608.08219v1 Announce Type: cross Abstract: Video anomaly detection (VAD) is a critical yet challenging task due to the complex and diverse nature of real-world scenarios. Traditional deep learn

model-releasesarxiv-cs-ai

11 Aug 2026

X2C: A Dataset Featuring Nuanced Facial Expressions for Realistic Humanoid Imitation

arXiv:2505.11146v3 Announce Type: replace-cross Abstract: Fine-grained facial expression transfer from humans to humanoid agents presents a unique pattern recognition challenge due to the significant

11 Aug 2026

Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques

arXiv:2608.06609v1 Announce Type: new Abstract: Automated item evaluation (AIE) refers to the use of computational methods to assess item quality without requiring manual expert review or field testin

Blind to the Pivotal Vote: Aggregate Independence Metrics Miss Where Verification Actually Helps

arXiv:2608.06940v1 Announce Type: new Abstract: LLM judge panels are a standard evaluation tool, but prior work reports highly correlated panel errors: nine judges provide roughly the effective inform

Cascade: Exploiting SLO-Aware latency budget for fair and high goodput LLM inference serving

arXiv:2608.06557v1 Announce Type: cross Abstract: The reasoning and agentic capabilities of large language models have expanded the range of applications they support, from short interactive exchanges

I Seek You in Videos: Identity-Conditioned Queries for Person-Centric Video Reasoning

arXiv:2608.07417v1 Announce Type: cross Abstract: Real-world video reasoning often involves multimodal, multi-source inputs, whereas existing video reasoning tasks typically assume a simplified video-

Hardware

Scalable High-Fidelity Macromolecular Docking for GPU-Accelerated Supercomputers

arXiv:2608.07078v1 Announce Type: cross Abstract: Flexible macromolecular docking offers high-fidelity predictions of biomolecular interactions, but remains prohibitively expensive at scale. Among exi

hardwarearxiv-cs-ai

TradeVerse: A Longitudinal Benchmark of Political Negotiation in International Trade

arXiv:2608.06549v1 Announce Type: cross Abstract: LLMs are increasingly being applied to tasks involving institutional and political texts, but existing benchmarks evaluate them on isolated documents

GST-Bench: Can VLMs Develop Global Spatial Awareness from Video?

arXiv:2608.05747v1 Announce Type: new Abstract: Spatial intelligence is fundamental to embodied agents, yet existing benchmarks focus on local spatial perception from single or few viewpoints, overloo

HERALD: Counterfactual Audits and Minimal Repairs for Proof-of-Retrieval Rewards

arXiv:2608.06012v1 Announce Type: new Abstract: Search-agent rewards mix answer quality, citation grounding, tool cost, and anti-hacking terms; a high score therefore need not imply that cited evidenc

Improving the Realism of Synthetic Clinical Benchmarks Under Utility Constraints

arXiv:2608.06265v1 Announce Type: new Abstract: Synthetic clinical benchmarks for enterprise AI agents can pass existing utility checks and still remain structurally unrealistic, especially in privacy

LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models

arXiv:2608.05706v1 Announce Type: new Abstract: World models enable agents to perform forward rollout and planning without real-world interaction. However, their application in open-world embodied int

safetyarxiv-cs-cv

Project2Task: Graph-Guided Project-Level Planning for Autonomous Research

arXiv:2608.05225v1 Announce Type: new Abstract: Research agents can increasingly search literature, propose hypotheses, generate code, run experiments, and draft manuscripts from a single topic. Howev

Local Ai

TRW: TRACE-RealWorld---An Auditable Consistency Contract for World Models as Materialized Views

arXiv:2607.21910v2 Announce Type: replace Abstract: World models let agents plan against predicted physical state, but that state drifts; re-observation is costly and delayed, and repair can fail. We

local-aiarxiv-cs-ai

Applications

VLMs for Videogame Data Annotation

arXiv:2608.05949v1 Announce Type: new Abstract: Vision Language Models (VLMs) and Artificial Intelligence (AI) agents have revolutionized how engineers approach complex problems in real-world applicat

applicationsarxiv-cs-ai

When History Lies: Evaluating and Improving Tool Use under Misleading Multi-Turn Histories

arXiv:2608.06057v1 Announce Type: new Abstract: Tool-calling agents infer task state from accumulated dialogue and tool traces. In persistent interactions, however, historical traces may remain struct

Corrigibility Transformation: Constructing Goals That Accept Updates

arXiv:2510.15395v2 Announce Type: replace Abstract: An AI agent will learn a desired goal more effectively if it does not resist the training process, but many partially learned goals incentivize an A

Research

Emergence of Hierarchical Emotion Organization in Large Language Models

arXiv:2507.10599v3 Announce Type: replace-cross Abstract: As large language models (LLMs) increasingly power conversational agents, understanding how they model users' emotional states is critical for

researcharxiv-cs-ai

Research

MemFly: On-the-Fly Memory Optimization via Information Bottleneck

arXiv:2602.07885v2 Announce Type: replace Abstract: Long-term memory enables large language model agents to tackle complex tasks through historical interactions. However, existing frameworks encounter

researcharxiv-cs-ai

Overcoming Statistical Bias in Action-Controllable World Models

arXiv:2608.04653v1 Announce Type: new Abstract: Action-conditioned world models aim to predict how visual environments evolve under an agent's actions. Yet future frames are often highly predictable f

safetyarxiv-cs-cv

Reward Structure Shapes the Interaction Between Episodic Exploration and Neural Memory in Reinforcement Learning

arXiv:2608.05111v1 Announce Type: new Abstract: In partially observable reinforcement learning, agents face a dual bottleneck: they must explore to encounter rewarding states and retain that experienc

SpikingNav: Robust Embodied Navigation with Spiking Neural Policies

arXiv:2608.05078v1 Announce Type: new Abstract: Embodied navigation requires an agent to make sequential decisions from egocentric observations in a physical environment. Existing Artificial Neural Ne

safetyarxiv-cs-ro

Teaching Foundation Models to Read mmWave: Pose-Guided Kinematic Representation for Human Behavior Understanding

arXiv:2608.04127v1 Announce Type: new Abstract: Large language model agents need to perceive human behavior in physical environments. Millimeter-wave (mmWave) radar provides a privacy-friendly and con

CARE-Bench: Benchmarking Patient-Facing LLM Triage

arXiv:2608.03731v1 Announce Type: new Abstract: Patient-facing medical LLMs and agents increasingly answer symptom questions before clinician contact, where the key safety question is what action the

FedCritic-MIMO: Communication-Efficient Serverless Federated Critic Learning for Massive-MIMO Resource Control in Open and Disaggregated 6G RANs

model-releasesarxiv-cs-lg

arXiv:2608.03852v1 Announce Type: new Abstract: This paper proposes FedCritic-MIMO, a communication-efficient serverless federated multi-agent reinforcement learning framework for AI-native resource c

Flying over The Uncertain Nature (FORTUNE): Intelligent and Humanistic 3D Path Planning for Low-Altitude Collaboration

arXiv:2608.03408v1 Announce Type: new Abstract: The proliferation of low-altitude intelligent agents is increasing the demand for timely and socially responsible collaborative sensing in dynamic urban

safetyarxiv-cs-ro

GUI-Lens: Coarse-to-Fine Cropping for GUI Grounding with General-Purpose VLMs

arXiv:2608.03270v1 Announce Type: cross Abstract: GUI grounding maps natural-language instructions to click locations and is essential for reliable GUI agents. The task remains difficult on high-resol

Tutorials

Neurosymbolic Reasoning with Incremental Knowledge for Sample Efficient Hierarchical Reinforcement Learning

arXiv:2608.02993v1 Announce Type: new Abstract: (Flat) Reinforcement Learning (RL) agents face significant challenges in environments with sparse rewards that require long-horizon reasoning. A compell

tutorialsarxiv-cs-ai

UniNav: A Unified World-Action Diffusion Model for Visual Navigation

arXiv:2608.03244v1 Announce Type: new Abstract: Image-goal visual navigation is a fundamental capability for embodied agents. Existing navigation policies efficiently predict waypoint trajectories but

When Search Teaches Style: Causal Internalization of Tactical Priors in AlphaZero

arXiv:2504.14636v3 Announce Type: replace-cross Abstract: AlphaZero is normally evaluated as one agent: a policy-value network fused with Monte Carlo tree search. That fusion hides a causal question.

A Spectral Filtering Approach to Regret Analysis of Distributed Online Control for Linear Dynamical Systems

arXiv:2608.02375v1 Announce Type: cross Abstract: This paper studies the distributed online control problem over a network of linear time-invariant (LTI) systems in the presence of adversarial disturb

DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Surveys

model-releasesarxiv-cs-cl

arXiv:2601.15307v2 Announce Type: replace-cross Abstract: The rapid development of automated survey generation technology has made it increasingly important to establish a comprehensive benchmark to e

HindSearch: Trajectory-Level Hindsight Critique for Search-Augmented Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2608.01597v1 Announce Type: new Abstract: Search-augmented LM agents are typically trained with a binary exact-match reward, which throws away most of what a failed trajectory tells us about why

Local Ai

Language Equality has a Price: A Systematic Investigation of Multi-turn LLM Performance for EU-24+

arXiv:2608.01395v1 Announce Type: new Abstract: We evaluate large language models (LLMs) as language agents playing goal-directed dialogue games in self-play across 30 languages: the 24 official EU la

local-aiarxiv-cs-cl

Latent-Centroid Steering: Single-Pass Classifier-Free Guidance for Command-Aligned Autonomous Driving

arXiv:2608.00237v1 Announce Type: new Abstract: Vision-language models (VLMs) have recently emerged as a promising paradigm for end-to-end autonomous driving, enabling agents to map multimodal inputs

Move What Matters: Parameter-Efficient Domain Adaptation via Optimal Transport Flow for Collaborative Perception

arXiv:2602.11565v5 Announce Type: replace Abstract: Efficient domain adaptation remains a fundamental challenge for deploying multi-agent systems across diverse environments in Vehicle-to-Everything (

RADAR: Rubric-Aware Dependency and Redundancy Analysis for LLM-as-Judge Evaluation

model-releasesarxiv-cs-cl

arXiv:2608.01810v1 Announce Type: new Abstract: Rubric-based LLM-as-judge pipelines often assume that evaluation criteria provide independent signals. In practice, however, criteria can be behaviorall

Toward Plasticity-Preserving KL Regularization for Capability Retention in LLM Reinforcement Learning

arXiv:2608.01743v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a central paradigm for large language model (LLM) post-training, but optimization toward new objectives can deg

safetyarxiv-cs-cl

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills

arXiv:2608.01851v1 Announce Type: new Abstract: Robot learning is splitting into two bets: policies that bake competence into frozen weights (vision-language-action, or VLA, models), and agents that w

safetyarxiv-cs-ro

Local Ai

CPInj: Uncovering Prompt Injection Risks in Textual Collaborative Prompt Optimization

arXiv:2607.18622v2 Announce Type: replace-cross Abstract: Textual Collaborative Prompt Optimization (TCPO) extends TextGrad (Yuksekgonul et al., 2025) to a decentralized setting by allowing multiple c

local-aiarxiv-cs-ai

ModelEquivBench: Certifying Multi-Relational Evaluation of LLM-Generated Optimization Models

arXiv:2607.29431v1 Announce Type: new Abstract: Large language models increasingly generate optimization models from natural language, but existing evaluation often reduces a generated model and its g

Retrieval-Driven Training-Free AI-Generated Video Attribution

arXiv:2607.28955v1 Announce Type: cross Abstract: AI-generated videos are becoming increasingly realistic and difficult to distinguish from authentic ones, which facilitates malicious misuse and poses

When Does On-Policy Interaction Help? Representational Tradeoffs in Value-Based Imitation Learning

arXiv:2607.29617v1 Announce Type: cross Abstract: Imitation learning (IL)---training an agent to replicate expert behavior from demonstrations---underpins applications from robotics to language model

AI-assisted pre-review of open-source software submissions: an experience report from BOSC 2026

arXiv:2607.27228v1 Announce Type: new Abstract: Most conferences rely on peer-review of submissions, but as generative AI makes it easier than ever to prepare submission materials, some conferences ar

safetyarxiv-cs-cl

Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding

arXiv:2607.28516v1 Announce Type: new Abstract: Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus

Hierarchical Multilevel Monte Carlo for Order-Optimal Neural Actor-Critic in Average-Reward CMDPs

arXiv:2607.28390v1 Announce Type: new Abstract: Constrained Markov Decision Processes (CMDPs) provide a natural framework for reinforcement learning in safety-critical applications, where agents maxim

TEA-AgriVLN: Traversability Estimation Alarm for Agricultural Vision-and-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2607.28474v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires an agent to follow a natural language instruction, predicting a sequence of