agents

A Multi-Agent LLM System for Automated Tuning of Specialized Neural Network Models

arXiv:2610.13663v1 Announce Type: new Abstract: Many machine learning approaches are two-level: an expert selects a class of methods, within this class the choice of key components is critical and usu

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Agents

Agent4Spec: An LLM-based Agentic System to Optimize API Specifications through Automated Validation and Market Analysis

DGX agent

arXiv:2610.13273v1 Announce Type: cross Abstract: API specifications serve as critical documentation for modern software development, directly impacting integration efficiency and client code generati

agentsarxiv-cs-ai

12 Oct 2026

Agentic Large Language Models

arXiv:2610.13455v1 Announce Type: new Abstract: Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has

ARTIS: Agentic Risk-Aware Test-Time Scaling via Iterative Simulation

arXiv:2602.01709v3 Announce Type: replace Abstract: Current test-time scaling (TTS) techniques enhance large language model (LLM) performance by allocating additional computation at inference time, ye

Beyond the Snowflakes: Disentangling Weather Effects from Confounding Meta-Factors in LiDAR Object Detection

arXiv:2610.13891v1 Announce Type: cross Abstract: Light Detection and Ranging (LiDAR) is critical for autonomous perception, yet its performance is known to degrade in adverse weather. While existing

Can Failed Trajectories Reveal Where Agents Go Wrong? Agentic Failure Attribution Without Step-Level Labels

arXiv:2610.13105v1 Announce Type: new Abstract: Failure attribution for LLM agents aims to identify decisive steps responsible for task failure, which is critical for debugging and improving agentic s

CB-Orchestrator: Adaptive Workflow Optimization for LLM Agents via Contextual Bandits

arXiv:2610.13064v1 Announce Type: new Abstract: Large Language Model (LLM) agents have demonstrated remarkable capabilities in tackling complex tasks through agentic workflows. However, manually desig

Co-Modifying Application Code and Deployment Infrastructure: A Causal Study of AI Agent Pull Requests

arXiv:2610.12849v1 Announce Type: cross Abstract: Current software engineering agents are evaluated predominantly inside isolated sandboxes against synchronous local tests. However, deploying features

Collective Autonomous Vehicle Routing Needs Social Awareness for Coexistence with Human Drivers

arXiv:2610.13439v1 Announce Type: cross Abstract: Collective Autonomous Vehicle (AV) route choices in real-world traffic networks can create externalities for Human-Driven Vehicles (HDVs), as routes t

Competence-Aware Orchestration for LLM-Based Multi-Agent Systems

arXiv:2610.13144v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have emerged as a promising paradigm for enhancing complex reasoning through role specialization and collaboration,

Cubic Spline Interpolation for Smooth Trajectory Generation in Autonomous Motion Systems

arXiv:2610.12826v1 Announce Type: new Abstract: We presented a program that automates the construction and solution of the cubic spline interpolation problem for a sequence of position-time waypoints,

Data-Driven Stochastic Optimal Control in Reproducing Kernel Hilbert Spaces

arXiv:2407.16407v3 Announce Type: replace-cross Abstract: This paper proposes a fully data-driven approach for optimal control of nonlinear control-affine systems represented by a stochastic diffusion

Does Knowledge About Perceptual Uncertainty Help an Agent in Automated Driving?

arXiv:2502.11864v2 Announce Type: replace-cross Abstract: Agents in real-world scenarios like automated driving deal with uncertainty in their environment, in particular due to perceptual uncertainty.

Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback

arXiv:2610.12549v1 Announce Type: cross Abstract: Embodied coding agents construct robot policies from natural-language instructions by generating executable programs and refining them from execution

Forgetting is Not Always Bad: A Neuro-Inspired Memory Repair Mechanism for Poisoned LLM Agents

arXiv:2610.13267v1 Announce Type: new Abstract: Large language model (LLM) agents are highly vulnerable to memory-poisoning attacks. Existing defenses primarily rely on external modules for either sta

Humanize MLE Agents: Multi-Agent Session Alternation Beyond Single-Agent Limits

arXiv:2610.13494v1 Announce Type: new Abstract: Existing LLM-based agent approaches for long-horizon machine learning engineering (MLE) often use context engineering, implemented through custom harnes

Incremental Retrieval-Augmented Generation for Human-in-the-Loop Decision Support

arXiv:2610.12666v1 Announce Type: cross Abstract: We introduce iRAG, a human-in-the-loop decision-support system combining Retrieval-Augmented Generation (RAG) with Hybrid Decision-Making. Unlike conv

Infinitesimal Operator World Models: Finite-Sample Guarantees for Offline Reinforcement Learning

arXiv:2511.10383v2 Announce Type: replace-cross Abstract: Continuous-time stochastic processes underlie many natural and engineered systems. In healthcare, autonomous driving, and industrial control,

JANUS: Enhancing Long-Horizon Autonomous Research with Co-Evolving World Models

arXiv:2610.13194v1 Announce Type: new Abstract: Long-horizon autonomous research has shown promise in accelerating scientific progress through sustained cycles of hypothesis generation, implementation

Know What You Don't Know: Agentic Data Synthesis by Evolving Generation Space for Closed-Loop Learning

arXiv:2610.12593v1 Announce Type: new Abstract: The continued improvement of large language models increasingly depends on synthetic experience, yet effective data synthesis for interactive agents req

Large Language Models, Machine-Assisted Cultural Analytics, and the Agentic Turn

arXiv:2610.12792v1 Announce Type: cross Abstract: Technologies like large language models make it easier to convert cultural material into analyzable variables, while LLM-driven agentic systems extend

Mapless, Stabilizing, and Anti-Stuck Flipper Control for Articulated Tracked Robots

arXiv:2610.13838v1 Announce Type: new Abstract: Nearly every autonomous or semi-autonomous flipper controller assumes access to an elevation map of the terrain under and in front of the robot. The ter

MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS

arXiv:2610.13772v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) has become a prominent research direction, particularly within collective robotics, where the ARGoS simulato

Meta-Reflective Evolution Effectively Improves Production AI Systems

arXiv:2610.12794v1 Announce Type: cross Abstract: Large Language Model (LLM)-guided evolutionary optimization has successfully improved prompts, programs, and even entire AI systems. Most optimization

PACT: Privileged Trace Co-Training for Multi-Turn Tool-Use Agents

arXiv:2606.16215v2 Announce Type: replace-cross Abstract: Multi-turn tool-use agents must reason, call tools, and adapt to observations across several interaction turns. Post-training such agents is c

Prediction-Informed Landing Window Planning for UAV Landing on USV in High Sea States

arXiv:2610.13190v1 Announce Type: cross Abstract: Autonomous landing of unmanned aerial vehicle (UAV) on unmanned surface vehicle (USV) is difficult in high sea states. Existing hierarchical landing m

ProgramGym: Scaling Training Environments for Long-Horizon Program Reproduction Agents

arXiv:2610.13395v1 Announce Type: cross Abstract: Coding agents are increasingly used to build programs from scratch as software engineers do rather than to resolve issues within a repository or to ge

Recurrent Harness for Agentic Continual Learning

arXiv:2610.12668v1 Announce Type: cross Abstract: Language model agents increasingly operate over long interaction streams, requiring online adaptation to distribution shifts through continual learnin

Reflective Prompt Optimization of a Deep-Research Agent: A Topic-Disjoint, Multi-Seed Protocol for Measuring Transferable Gains and Prompt-Level Overfitting

arXiv:2610.12601v1 Announce Type: new Abstract: Prompt optimization is an attractive alternative to reinforcement learning for adapting language-model agents, since it is cheap and produces human-read

Scaling Empowered Agents

arXiv:2610.13002v1 Announce Type: new Abstract: Empowerment measures the capacity of an agent to actively control its environment. In this work, we explain the connection between skill learning and em

SEEDS: Preview-Guided Evidence Admission for Search Agents

arXiv:2610.12932v1 Announce Type: new Abstract: Search agents extend large reasoning models with multi-round access to external knowledge, yet most existing systems largely conflate retrieving evidenc

Sustainable Cloud-Fog-Edge Systems for Smart Buildings: Algorithmic Adaptation under Memory Constraints and Dynamic Orchestration Strategies

arXiv:2610.13307v1 Announce Type: new Abstract: The escalating environmental footprint of the Information and Communication Technol- ogy (ICT) sectorwith global Data Center electric- ity usage potenti

SWE-Critix: Post-Training Generalist Verifiers for Assessing Coding-Agent Trajectories

arXiv:2610.13356v1 Announce Type: new Abstract: Coding agents are increasingly deployed for end-to-end software engineering tasks, where a readily available oracle evaluator that defines the success c

SynAct: Synergistic Active Feedback Learning for LLM Agents

arXiv:2610.12651v1 Announce Type: new Abstract: LLM agents executing multi-step workflows fail in two fundamentally different ways: recoverable slips, which further attempts can repair, and knowledge

TelcoAgent: A Scalable 5G Multi-KPM Forecasting With 3GPP-Grounded Explainability

arXiv:2606.19821v2 Announce Type: replace Abstract: Key Performance Measurement (KPM) forecasting is essential for proactive network management of 5G and next-generation telecom networks. However, exi

The value of information and the emergence of communication in evolved e-puck robots

arXiv:2610.13118v1 Announce Type: new Abstract: We study when communication emerges between autonomous agents and what role an innate action selection architecture plays. Two e-puck robots, reconstruc

Web$hell: A Unified Interface for Agentic Web Access

arXiv:2610.13416v1 Announce Type: new Abstract: Large language model (LLM) agents are becoming direct users of the open web. As they take on increasingly complex and information-intensive tasks, effec

When Faster Decisions Do Not Make Better Agents: An Empirical Study of Jev in Agent Workflows

arXiv:2610.13092v1 Announce Type: new Abstract: AI agents depend on repeated decisions to accomplish tasks, with large language models (LLMs) commonly serving as their core decision makers. The recent

Work2Skill: Capturing Human GUI Experience for Reusable Agent Skill Induction

arXiv:2610.12984v1 Announce Type: new Abstract: Computer-use agents can perform increasingly complex GUI tasks, yet unfamiliar software and workflows requiring human domain knowledge remain challengin

X-AgentRed: Red-Teaming Personal Agents in Evolving Multi-Service Ecosystems

arXiv:2610.13886v1 Announce Type: new Abstract: Personal agents increasingly connect to services across the web and applications by using tools. As the effects of their actions accumulate and interact

Accurate but Not Humble: Evaluating Epistemic Humility in LLM Agents under Knowledge Conflict

arXiv:2610.12360v1 Announce Type: new Abstract: When retrieved evidence contradicts an agent's prior beliefs, does it revise its answer, acknowledge uncertainty, or persist with an incorrect conclusio

Agent-Controlled Forgetting for Tool-Using Agents: Reversible Context Curation in Practice

arXiv:2610.10590v1 Announce Type: new Abstract: Tool-using agents repeatedly carry observations whose useful content can be much smaller than their original payload. We study agent-controlled forgetti

AgentEvolver: System-Wide Self-Evolution Through Task Execution

arXiv:2610.11613v1 Announce Type: new Abstract: An agent can complete a task without improving how it works. Turning task experience into reusable capability requires connecting the changed component

AgentFly: Scaling Agentic Reinforcement Learning with Unified Resource System

arXiv:2507.14897v2 Announce Type: replace Abstract: Methods to build LLM agents have evolved from prompt engineering and supervised finetuning to agentic reinforcement learning (agentic RL). However,

Attention when you need

arXiv:2501.07440v3 Announce Type: replace-cross Abstract: Paying attention improves performance, but attention is metabolically costly, so how should a resource-efficient agent allocate it? We study o

Autonomous thermodynamic cycles via robotic mobility and sensing

arXiv:2610.11667v1 Announce Type: cross Abstract: Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work. However, these

Back in Style: A Sociolinguistic Approach to Authoring and Measuring Persona Fidelity in User Simulation

arXiv:2610.10988v1 Announce Type: new Abstract: As agentic systems gain commercial popularity, user simulators increasingly serve as measurement instrument for their evaluation. However, the fidelity

Best of Both Worlds in Federated LSA: Speedup When Possible, Personalization Always

arXiv:2610.11555v1 Announce Type: new Abstract: We study personalized federated linear stochastic approximation (LSA), a framework which notably encompass personalized temporal difference learning. In