Search: “agents”

Large Language Models Approach Expert Pedagogical Quality in Math Tutoring but Differ in Instructional and Linguistic Profiles

arXiv:2512.20780v3 Announce Type: replace Abstract: Recent work has explored the use of large language models (LLMs) to generate tutoring responses in mathematics, yet it remains unclear how closely t

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Agents

PIRS: Physics-Informed Reward Shaping for SAC-Based Building Energy Management

DGX agent

arXiv:2605.28232v1 Announce Type: new Abstract: Occupant comfort and grid-aware energy efficiency are competing objectives whose joint optimization depends critically on how reward functions are speci

agentsarxiv-cs-ai

28 May 2026

SCALE-COMM: Shared, Contrastively-Aligned Latent Embeddings for MARL Communication

arXiv:2605.27532v1 Announce Type: new Abstract: Emergent communication enables partially observant Autonomous Mobile Robots (AMRs) to coordinate effectively in decentralized multi-agent reinforcement

safetyarxiv-cs-ro

Securing Retrieval-Augmented Generation: A Taxonomy of Attacks, Defenses, and Future Directions

arXiv:2604.08304v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external knowledge, but this access path also introduces securi

Local Ai

The Energy Blind Spot: NVIDIA's Flagship Edge AI Hardware Cannot Support Process-Level Energy Attribution

arXiv:2605.27599v1 Announce Type: cross Abstract: Agentic AI workloads - where a single user goal triggers multi-step orchestration, tool calls, retries, and failure recovery - are being targeted for

local-aiarxiv-cs-ai

Verifiable Benchmarking of Long-Horizon Spatial Biology

arXiv:2605.28065v1 Announce Type: new Abstract: AI agents are increasingly useful for biological data analysis, but existing benchmarks mostly test broad biological knowledge, executable workflows, or

VibeSearchBench: Benchmarking Long-horizon Proactive Search in the Wild

arXiv:2605.27882v1 Announce Type: cross Abstract: LLM-based agents score well on search benchmarks, yet real users consistently find results unsatisfying, revealing a persistent evaluation-experience

Can Broad Biomedical Knowledge be Contextualized into Scenario-Grounded Propositions?

arXiv:2605.27082v1 Announce Type: new Abstract: Biomedical discovery often requires connecting broad biomedical knowledge with specific experimental or clinical data. Background knowledge suggests rel

Cost of Structural Learning Under Censored Feedback: A Threshold-Bandit Approach

arXiv:2605.27076v1 Announce Type: cross Abstract: In many multi-agent applications, tasks yield rewards only when executed by a coalition meeting an unknown size threshold; otherwise, feedback is full

safetyarxiv-cs-lg

Design First, Code Later: Aesthetically Pleasing Template-Free Slides Generation

arXiv:2605.26451v1 Announce Type: cross Abstract: Producing presentation slides automatically entails coordinating narrative structure with page-level graphic design under strict spatial constraints.

agentsarxiv-cs-cv

Disentangled Representation Learning through Unsupervised Symmetry Group Discovery

arXiv:2603.11790v3 Announce Type: replace Abstract: Symmetry-based disentangled representation learning leverages the group structure of environment transformations to uncover the latent factors of va

Learning GUI Grounding with Spatial Reasoning from Visual Feedback

arXiv:2509.21552v2 Announce Type: replace-cross Abstract: Graphical User Interface (GUI) grounding is commonly framed as a coordinate prediction task -- given a natural language instruction, generate

Neural Bayesian Sequential Routing

arXiv:2605.26147v1 Announce Type: new Abstract: Human decision-making is sequential and uncertainty-aware, yet standard neural networks often rely on static, dense forward computation with limited vis

Optimal Rates for Feasible Payoff Set Estimation in Games

arXiv:2602.04397v2 Announce Type: replace-cross Abstract: We study a setting in which two players play a (possibly approximate) Nash equilibrium of a bimatrix game, while a learner observes only their

Persona Generators: Generating Diverse Synthetic Personas for Arbitrary Contexts

arXiv:2602.03545v2 Announce Type: replace Abstract: Evaluating AI systems that interact with humans requires understanding their behavior across diverse user populations, but collecting representative

PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design

arXiv:2605.26543v1 Announce Type: new Abstract: Polymer discovery is central to fields ranging from energy storage to biomedicine, but it is hindered by an astronomically large chemical design space a

Telenor Nordics Customer Service self-help corpus

arXiv:2605.26891v1 Announce Type: new Abstract: This paper presents a multilingual customer service self-help corpus comprising 1,122 manually validated documents in Finnish, Danish, Norwegian, and Sw

When Does Adaptive Guidance Help? Belief-Aware Privileged Distillation for Autonomous Driving Under Partial Observability

arXiv:2605.26155v1 Announce Type: cross Abstract: Guided Soft Actor-Critic (GSAC) distills knowledge from a privileged full-state teacher to a partial-observation student for autonomous driving, but u

AGI Requires a Coordination Layer on Top of Pattern Repositories

arXiv:2512.05765v2 Announce Type: replace Abstract: In this paper we argue that influential critiques dismissing Large Language Models (LLMs) as a dead end for AGI misidentify the bottleneck: they con

Anisotropic Diffusion-Driven Ergodic Coverage in Multi-Robot Systems

arXiv:2605.24125v1 Announce Type: new Abstract: We consider the problem of combining potential field and ergodic search on multi-robot systems. Traditional ergodic search algorithms use metrics for er

Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork

arXiv:2605.24423v1 Announce Type: new Abstract: In-Context Reinforcement Learning (ICRL) has enabled foundation agents to adapt instantaneously to novel tasks, yet its efficacy in Ad-Hoc Teamwork (AHT

CVEvolve: Autonomous Algorithm Discovery for Unstructured Scientific Data Processing

arXiv:2605.11359v2 Announce Type: replace Abstract: Scientific data processing often requires task-specific algorithms or AI models, creating a barrier for domain scientists who need to analyze their

Drift-Resistant Navigation World Model with Anchored Epipolar Guidance

arXiv:2605.24761v1 Announce Type: cross Abstract: We propose Drift-Resistant Navigation World Model, a generative model that mitigates both perceptual drift and geometric drift in conventional rollout

From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems

arXiv:2605.23955v1 Announce Type: new Abstract: Deploying machine learning in regulated financial environments -- credit risk, fraud detection, and anti-money laundering -- exposes critical vulnerabil

GRAIL: AI translation for scientists application workflow on satellite data

arXiv:2605.24784v1 Announce Type: new Abstract: Domain scientists increasingly develop Python scripts to analyze satellite imagery but they lack scalability to large-scale data. This paper demonstrate

Machine Psychometrics: A Mathematical Psychology of Artificial Intelligence

arXiv:2605.23952v1 Announce Type: new Abstract: Artificial agents now generate behavior rich enough to invite trust, surprise, and concern, yet our evaluation tools still privilege capability scores o

safetyarxiv-cs-ai

Multi-market value-stacking: Battery control for combined imbalance participation and non-uniform FCR bidding

arXiv:2605.23964v1 Announce Type: cross Abstract: The growing share of Renewable Energy Sources (RES) in modern power systems increases both grid imbalances and frequency deviations, reinforcing the n

Persuasion Should be Double-Blind: A Multi-Domain Dialogue Dataset With Faithfulness Based on Causal Theory of Mind

arXiv:2502.21297v2 Announce Type: replace Abstract: Persuasive dialogue is central to human communication, yet existing datasets often rely on a single language model generating both roles, producing

IntentionNav: A Benchmark for Intent-Driven Object Navigation from Implicit Human Instruction

model-releasesarxiv-cs-cv

arXiv:2605.23187v1 Announce Type: new Abstract: Existing object navigation benchmarks usually tell an embodied agent which object category to find, such as microwave or chair. Human-facing embodied AI

25 May 2026

LACY: A Vision-Language Model-based Language-Action Cycle for Self-Improving Robotic Manipulation

arXiv:2511.02239v2 Announce Type: replace-cross Abstract: Learning generalizable policies for robotic manipulation increasingly relies on large-scale models that map language instructions to actions (

25 May 2026

SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research

arXiv:2605.22878v1 Announce Type: new Abstract: The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmen

25 May 2026

Abstraction for Offline Goal-Conditioned Reinforcement Learning

arXiv:2605.22711v1 Announce Type: new Abstract: Markov Decision Processes (MDPs) often exhibit significant redundancy due to symmetries and shared structure across state-goal pairs in real-world Goal-

23 May 2026

Harnesses for Inference-Time Alignment over Execution Trajectories

arXiv:2605.21516v1 Announce Type: new Abstract: Harness engineering has emerged as an important inference-time technique for large language model (LLM) agents, aiming to improve long-term performance

safetyarxiv-cs-lg

23 May 2026

Skill Weaving: Efficient LLM Improvement via Modular Skillpacks

arXiv:2605.22205v1 Announce Type: cross Abstract: Large language models increasingly require specialization across diverse domains, yet existing approaches struggle to balance multi-domain capacities

23 May 2026

Flying Together: Human-Guided Immersive Shared Control for Aerial Robot Teams in Unknown Environments

arXiv:2605.21680v1 Announce Type: new Abstract: While autonomous multi-robots can achieve safe and coordinated navigation, they often struggle to adapt to unforeseen conditions and to capture operator

GA-VLN: Geometry-Aware BEV Representation for Efficient Vision-Language Navigation

arXiv:2605.22036v1 Announce Type: new Abstract: Despite significant progress in Vision-Language Navigation (VLN), existing approaches still rely on dense RGB videos that produce excessive patch tokens

agentsarxiv-cs-cv

LIDSA: Cognitive Arbitration for Signal-Free Autonomous Intersection Management

arXiv:2605.12321v2 Announce Type: replace Abstract: Large language models (LLMs) show strong potential for Intelligent Transportation Systems (ITS), particularly in tasks requiring situational reasoni

Lower Bounds for Advection-Diffusion Equations: An Exploration with AI-Generated Proofs

arXiv:2605.20623v1 Announce Type: cross Abstract: We establish explicit lower bounds for advection-diffusion equations in three settings: a polynomial ot H^{-1} bound for inviscid shears with uin L^in

NaviAgent: Graph-Driven Bilevel Planning for Scalable Tool Orchestration

arXiv:2506.19500v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly act as function-call agents that invoke external tools to tackle tasks beyond their static knowledge

safetyarxiv-cs-cl

Stdlib or Third-Party? Empirical Performance and Correctness of LLM-Assisted Zero-Dependency Python Libraries

arXiv:2605.21405v1 Announce Type: cross Abstract: Third-party Python libraries introduce dependency management overhead, supply chain risk, and deployment friction in constrained environments. A natur

AI-Powered Facial Mask Removal Is Not Suitable For Identification

arXiv:2603.27747v2 Announce Type: replace Abstract: Recently, crowd-sourced online criminal investigations have used generative-AI to enhance low-quality visual evidence. In one high-profile case, soc

agentsarxiv-cs-cv

Beyond Words: Multimodal LLM Knows When to Speak

arXiv:2505.14654v2 Announce Type: replace-cross Abstract: Chatbots via large language models (LLMs) generate fluent responses but often struggle with when to speak, especially for brief, timely listen

Code Generation by Differential Test Time Scaling

arXiv:2605.20473v1 Announce Type: cross Abstract: Test-time scaling has emerged as a promising approach for improving code generation by exploring large solution spaces at inference time. However, exi

Compositional Transduction with Latent Analogies for Offline Goal-Conditioned Reinforcement Learning

arXiv:2605.20609v1 Announce Type: new Abstract: Compositional generalization is essential for reaching unseen goals under novel contextual variations in offline goal-conditioned reinforcement learning

Decoupling Communication from Policy: Robust MARL under Bandwidth Constraints

arXiv:2605.21085v1 Announce Type: cross Abstract: Communication enables coordination in multi-agent reinforcement learning (MARL), but many real-world applications, e.g., search-and-rescue with drone

safetyarxiv-cs-lg

Draw2Think: Harnessing Geometry Reasoning through Constraint Engine Interaction

arXiv:2605.20743v1 Announce Type: cross Abstract: Vision-language models solve geometry problems with rising accuracy, yet their intermediate states remain latent and unverifiable: a relation expresse

MC-Risk: Multi-Component Risk Fields for Risk Identification and Motion Planning

arXiv:2605.21406v1 Announce Type: new Abstract: We present MC-Risk, a planner-aligned, multi-component risk field on a bird's-eye-view grid that yields early, calibrated, and class-aware risk localiza

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