Search: “agents”

arXiv:2608.10103v1 Announce Type: cross Abstract: High-performance Tensor Core kernels rely on a low-level PTX pipeline built from asynchronous data movement with cp.async, warp-level matrix loads wit

hardwarearxiv-cs-ai

12 Aug 2026

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

The Deliberative Deficit: An Empirical Critique of LLMs in Democratic Discourse

DGX agent

arXiv:2608.10186v1 Announce Type: cross Abstract: LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems. Confidence in these deployments rests l

agentsarxiv-cs-ai

12 Aug 2026

A Communication-Efficient Digital Twin Framework for PSO-Based Swarm Navigation and Obstacle Avoidance

arXiv:2406.19930v4 Announce Type: replace Abstract: Swarm-based target localization in industrial environments faces two major challenges: navigating obstacle-rich spaces and managing intensive commun

agentsarxiv-cs-ro

Benchmarking In-context Experiential Learning Through Repeated Product Recommendations

model-releasesarxiv-cs-lg

arXiv:2511.22130v2 Announce Type: replace Abstract: To navigate ever-shifting real-world environments, agents must grapple with incomplete knowledge and adapt their strategies through experience. Howe

IntelliAudit: Using Large Language Models to Evaluate Audit Controls

arXiv:2608.07688v1 Announce Type: new Abstract: IT audits require auditors to judge whether heterogeneous organizational evidence satisfies semantic security and compliance controls. This judgment is

Skills in Weights, Memory in Code: Hybrid Learning for Memory-Dependent Robot Manipulation

arXiv:2608.09410v1 Announce Type: new Abstract: Modern vision-language-action (VLA) policies have acquired broad manipulation skills, but typically generate each action chunk from the current observat

agentsarxiv-cs-ro

The Capability Ladder: A Curriculum-Modernization Framework for Workforce Readiness in the AI Era

arXiv:2608.07779v1 Announce Type: new Abstract: Artificial intelligence is changing the task composition of computing work faster than curricula and training typically adapt. This is a curriculum-fram

TRACE: TRajectory Attribution for Automated Context Engineering

arXiv:2608.09153v1 Announce Type: new Abstract: Production AI agents fail when their context sources -- system prompts, knowledge bases, tool descriptions, and procedural skills -- contain errors or g

VDGR-RAG: Vectors, Directories, Graphs, and Reflection Are All You Need for Unified Reasoning over Hierarchical Enterprise Knowledge

arXiv:2608.07994v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is essential for enterprise knowledge question answering (QA), particularly in domains with complex product documen

Research

Interaction Creates Dynamical AI Behavior Absent in Isolation

arXiv:2608.07457v1 Announce Type: new Abstract: What will happen when AI agents interact in daily life, e.g. when one AI starts bossing another around? We find a counterintuitive answer that opens new

researcharxiv-cs-ai

10 Aug 2026

Probing Visual Concepts in Lightweight Vision-Language Models for Automated Driving

arXiv:2603.06054v2 Announce Type: replace-cross Abstract: The use of Vision-Language Models (VLMs) in automated driving applications is becoming increasingly common, with the aim of leveraging their r

10 Aug 2026

Vehicle routing problem using deep reinforcement learning - A case study about truck planning in the industry

arXiv:2608.06668v1 Announce Type: new Abstract: As an important component of the supply chain industry, transportation has experienced rapid development in the past decade with the assistance of digit

10 Aug 2026

Computationally Efficient Collaborative Communication Via Regularity-Based Coarsening

arXiv:2608.05327v1 Announce Type: cross Abstract: Our results show that the existence of a short high-utility protocol already suffices for efficient communication. In particular, in a game with n pos

agentsarxiv-cs-lg

7 Aug 2026

Recursive Synthesis for Long-Horizon Terminal Tasks

arXiv:2608.05466v1 Announce Type: new Abstract: High-quality long-horizon training data for terminal agents is expensive to produce, often costing hundreds to thousands of dollars per task, because ea

7 Aug 2026

Improving Auto-Design of Neural PDE Solvers with a Domain-Specific Language

arXiv:2608.04384v1 Announce Type: new Abstract: Neural PDE solver auto-design is fundamentally a search-space representation problem. In the space of unrestricted Python programs, valid solvers form a

6 Aug 2026

OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling

arXiv:2608.05141v1 Announce Type: new Abstract: Context lengths of language models (LMs) have dramatically increased, driven by the demands for in-context learning, self-improvement, and long-horizon

6 Aug 2026

When Shared Rollouts Fail in Defensive Driving Evaluation: A NAVSIM Score Basis Audit

arXiv:2608.04896v1 Announce Type: new Abstract: Defensive driving scores are useful only when they preserve distinctions between policies that observe surrounding actors and those that do not. Re-simu

6 Aug 2026

Research

EFX Allocation In (Multi)Hypergraphs

arXiv:2608.03171v1 Announce Type: cross Abstract: We study fair allocations of indivisible goods among agents with heterogeneous monotone valuations. As fair we consider the allocations that are envy-

researcharxiv-cs-ai

From Routes to Steps: Separating Semantic Progress from Local Execution in Vision-and-Language Navigation

arXiv:2608.03143v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) requires an agent to follow a route-level instruction by executing its constituent steps from egocentric visual obs

safetyarxiv-cs-cv

Getting the Parameters Right: A Difficulty-Graded Benchmark and Probe-Guided Training for LLM Tool Calls

arXiv:2608.03071v1 Announce Type: new Abstract: Large language model agents derive much of their capability from tool use. Existing research on tool use has largely focused on selecting the right tool

PAIChecker: Uncovering and Checking PR-Issue Misalignment in SWE-Bench-Like Benchmarks

arXiv:2607.28587v2 Announce Type: replace-cross Abstract: SWE-bench-like benchmarks are widely used for evaluating LLM's issue resolution capability. They typically follow a common construction pipeli

Residual Flow Matching with Dynamic Cross-Interaction for 3D Multi-Person Motion Prediction

arXiv:2608.03379v1 Announce Type: new Abstract: 3D multi-person motion prediction requires modeling both individual kinematics and inter-person interactions. While Flow Matching is effective for multi

AI-Based Thesis Assessment: An Empirical Study of Human Evaluation Priorities and Their Impact on Automated Assessment

arXiv:2608.00717v1 Announce Type: cross Abstract: Rubric-based AI systems for thesis assessment use criterion weights to assign different levels of importance to evaluation criteria. These weights are

safetyarxiv-cs-cl

Applications

Don't Offer What Can't Be Done: Deterministic Executability Gating for LLM Skill Selection at Scale

arXiv:2608.01050v1 Announce Type: cross Abstract: Production LLM agents that select from large skill libraries face a limitation that semantic relevance alone cannot resolve: a skill may match a user'

applicationsarxiv-cs-cl

Humans Are More Diverse: Frontier LLMs Show Extreme Policies in Idealised AI Development Races

model-releasesarxiv-cs-lg

arXiv:2608.01193v1 Announce Type: cross Abstract: An AI development race creates a multi-agent safety dilemma. Each company can develop slowly and safely, or move faster while taking a risk that may r

Inference-Time Policy Alignment for Fair Reinforcement Learning

arXiv:2608.00175v1 Announce Type: new Abstract: Deep reinforcement learning (RL) agents achieve strong performance by optimizing scalar reward functions. However, once deployed, the policies of these

safetyarxiv-cs-lg

PB^2: Preference Space Exploration via Population-Based Methods in Preference-Based Reinforcement Learning

arXiv:2506.13741v2 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PbRL) has emerged as a promising approach for learning behaviors from human feedback without predefin

agentsarxiv-cs-lg

PredAct-Bench: Benchmarking Tool-Augmented Dialogue under Controlled Tool Noise

model-releasesarxiv-cs-cl

arXiv:2608.02372v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in task-oriented dialogue systems that support multi-step decision-making in high-stakes domains

RubricReviewer: From Direct Critique to Objective and Comprehensive Rubric-Driven Peer Review

arXiv:2608.00005v1 Announce Type: new Abstract: Peer review at major venues is under unprecedented submission pressure, motivating the use of large language models (LLMs) as review assistants. Existin

agentsarxiv-cs-cl

Data Turnstile: A Scalable Open Framework for Function-Calling Data Generation

model-releasesarxiv-cs-cl

arXiv:2607.29250v1 Announce Type: new Abstract: Small language models (SLMs) are attractive for agentic deployment due to low latency, reduced cost, and on-device privacy, yet they struggle with tool-

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat

arXiv:2607.29577v1 Announce Type: new Abstract: Games and simulators make valuable benchmarks by turning decisions into measurable outcomes, but many current suites under-test rules-rich tactical reas

UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation

arXiv:2607.29200v1 Announce Type: new Abstract: Ultrasound imaging has become increasingly widespread in clinical practice due to its portability, low cost and real-time capability, making ultrasound

ViSAGE: Constructing Self-Correcting Memories for Long-Form Video Understanding

arXiv:2607.28678v1 Announce Type: new Abstract: Multimodal agents operating in long-horizon environments must build and continually update multimedia memories to support entity-consistent, temporally

safetyarxiv-cs-ai

Albilich: Steerable Proof-State Orchestration for LLM-Based Mathematical Research with CAS Integration

model-releasesarxiv-cs-lg

arXiv:2607.27705v1 Announce Type: cross Abstract: Large language models can contribute useful ideas to mathematical research, yet long-horizon proof attempts remain difficult to coordinate, evaluate,

Local Ai

AlphaSchema: Exploring the Space of Trading Semantics for LLM-Based Alpha Mining

arXiv:2607.26642v1 Announce Type: new Abstract: Automated alpha mining has increasingly adopted large language model (LLM) agents for factor generation and iterative discovery. However, existing LLM-b

local-aiarxiv-cs-ai

Baikal: Structured Search for Deep Research over Data Lakes

model-releasesarxiv-cs-cl

arXiv:2607.27726v1 Announce Type: cross Abstract: Deep research over data lakes requires an LLM agent to investigate evidence across thousands of heterogeneous tables and passages to synthesize a repo

Model-Driven Requirements Configuration with Three-Valued Uncertainty Scoring

arXiv:2607.26220v1 Announce Type: cross Abstract: Context: Large Language Models (LLMs) offer natural-language flexibility for automated requirements elicitation but frequently generate structurally i

RefineSVG: Visual Feedback-Driven Reinforcement Learning for Image-to-SVG Generation

arXiv:2607.27699v1 Announce Type: new Abstract: We propose RefineSVG, a single-step closed-loop visual feedback framework that enables multimodal large language models (MLLMs) to perform high-fidelity

SkillSight: Calibrating Generic Content Bias for Skill Retrieval

arXiv:2607.18785v2 Announce Type: replace Abstract: As large language model agents gain access to increasingly large skill libraries, retrieving the right skill becomes critical to reliable capability

safetyarxiv-cs-ai

Research

Emergent Sparsity in Frozen Random CNN Feature Extractors for Deep Reinforcement Learning

arXiv:2607.26059v1 Announce Type: new Abstract: We report a striking phenomenon: deep reinforcement learning agents trained with frozen, randomly initialized CNN feature extractors spontaneously devel

researcharxiv-cs-lg

30 Jul 2026

RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deployment

arXiv:2607.26631v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports applications in healthcare, rehabilitation, fitness tracking, and smart environments. Ye

agentsarxiv-cs-lg

30 Jul 2026

SG-CoT: An Ambiguity-Aware Robotic Planning Framework using Scene Graph Representations

arXiv:2603.18271v3 Announce Type: replace Abstract: Ambiguity poses a major challenge to large language models (LLMs) used as robotic planners. In this letter, we present Scene Graph-Chain-of-Thought

agentsarxiv-cs-ro

30 Jul 2026

LLM-generated personalized nudges for improving pro-environmental behavior: Field evidence from resource conservation

arXiv:2604.03881v2 Announce Type: replace-cross Abstract: Encouraging pro-environmental behavior remains a major challenge for sustainable cities. Conventional feedback nudges can show individuals how

29 Jul 2026

Local Ai

Athena-Brain Technical Report: An Efficient Robot Brain for General Intelligence and Embodied Interaction

arXiv:2607.18985v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in language understanding, reasoning, and world knowledge. As embodied agents

local-aiarxiv-cs-ai

CallBench: A Benchmark for Dual-Goal Coordination in Phone Call Assistants

arXiv:2607.22635v1 Announce Type: new Abstract: Target-oriented dialogue systems have demonstrated strong capabilities in completing user goals through interactive conversations. However, existing stu

Cost-Aware Recovery-Pathway Identification and Bayesian Optimization for Autonomous Materials Discovery

arXiv:2607.23896v1 Announce Type: new Abstract: Autonomous laboratories automate experimental execution, but a campaign must also decide which recovery pathway merits optimization. We formulate this a

DeepFaith: Evidence-Grounded LLMs for Faithful Incident Reporting in Multi-Stage APT Defense

arXiv:2607.24348v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) are difficult to detect and interpret due to their multi-stage and stealthy nature. While recent autonomous defense

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video

arXiv:2607.23132v1 Announce Type: new Abstract: Assessing the severity of a traffic accident scenario is important to decide which emergency service to dispatch. Missing an ambulance dispatch on a ped