arXiv AI
Aug 7
Unified Agent: Managing Interactions across Devices
arXiv:2608. 05729v1 Announce Type: new Abstract: As capabilities rapidly increase, AI agents can move from running inside one app to acting across a user's devices over time.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv AI
Aug 7
The ethics of artificial intelligence in the life sciences: Universality, cultural diversity and an architecture of care
arXiv:2608. 05436v1 Announce Type: cross Abstract: The life sciences and health research have started to benefit from artificial intelligence, which raises ethical concerns that are real but, we argue, not special.
arXiv AI
Aug 7
SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries
arXiv:2608. 05604v1 Announce Type: cross Abstract: Large Language Models (LLMs) increasingly act as agents whose procedural knowledge is stored in reusable skill packages and loaded at inference time.
arXiv AI
Aug 7
F$^2$Agent: Financial Fusion of Agentic Intelligence for Multimodal Trading
arXiv:2608. 05668v1 Announce Type: cross Abstract: With increasingly diverse and heterogeneous information sources, effectively leveraging multimodal data is becoming pivotal for high-quality financial trading.
arXiv AI
Aug 7
Agentic self-driving microscopy benchmarks support qualification but do not necessarily generalize to unseen tasks
arXiv:2608. 05266v1 Announce Type: new Abstract: Large language model agents are increasingly being developed to control a wide range of scientific characterization tools including microscopes and synchrotron beamlines.
arXiv AI
Aug 7
When Privileged Guidance Misaligns: State-Matched Routing and Contextualized Self-Distillation for Multi-Turn Agents
arXiv:2608. 05219v1 Announce Type: new Abstract: Privileged on-policy distillation provides dense supervision for multi-turn agents by allowing a synchronized teacher to re-score the student's response at every turn with access to training-only references, such as successful trajectories.
arXiv AI
Aug 7
DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data
arXiv:2608. 05375v1 Announce Type: new Abstract: Clinical machine learning (ML) has the potential to support high-stakes medical decision-making, but reliable deployment is often constrained by scarce, heterogeneous, and temporal complexity.
arXiv AI
Aug 7
StepReflect: Structured UI Transition Reflection for Mobile GUI Agents
arXiv:2608. 05587v1 Announce Type: new Abstract: Autonomous mobile GUI agents require accurate action reflection for reliable long-horizon execution.
arXiv AI
Aug 7
Nonvisual Classification of Ground-Condition by Artificial Proprioception in an Amoeba-Inspired Autonomous Walking Robot
arXiv:2608. 05684v1 Announce Type: cross Abstract: Nonvisual classification of ground condition based on a multimodal sensing approach was investigated for an amoeba-inspired autonomous walking robot.
arXiv AI
Aug 7
BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics
arXiv:2601. 21800v4 Announce Type: replace Abstract: We introduce BioAgent Bench, an evaluation suite designed for measuring the performance and robustness of AI agents in common bioinformatics tasks.
arXiv AI
Aug 7
Resourced Authority A Mechanism-Design Model for Participatory Governance of Deployed AI Agents
arXiv:2608. 06353v1 Announce Type: cross Abstract: We give a formal mechanism design model for the continuous participatory governance of a deployed AI agent.
arXiv AI
Aug 7
iARCS: Iterative Agentic RL for Controllable 3D Scene Generation
arXiv:2608. 06161v1 Announce Type: new Abstract: Synthetic 3D scene generation is increasingly used as a data source for computer vision and embodied AI, but existing generators often optimize perceptual realism without reliably satisfying task-critical functional constraints.
arXiv Machine Learning
Aug 7
Worst-Case Distance-Aware Error Bounds for Neural Networks
arXiv:2510. 22021v3 Announce Type: replace Abstract: Safety-critical applications of machine learning require uncertainty estimates that support reliable worst-case analysis.
arXiv AI
Aug 7
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.
arXiv AI
Aug 7
WorldClaw: Agentic 3D Open-World Generation at Scale
arXiv:2608. 05248v1 Announce Type: new Abstract: Generating large-scale, freely explorable 3D worlds from open-ended text remains challenging because a system must jointly maintain global spatial coherence, rich local content, and explicit assets suitable for downstream editing and reuse.
arXiv AI
Aug 7
Agentic Software Issue Resolution with Large Language Models: A Survey
arXiv:2512. 22256v2 Announce Type: replace-cross Abstract: Software issue resolution aims to address real-world issues in software repositories based on natural language descriptions provided by users, and represents a key aspect of software maintenance.
arXiv Machine Learning
Aug 7
EvoHarness-RL: Learning Self-Evolving Runtime Harness for Long-Horizon LLM Agents
arXiv:2608. 05446v1 Announce Type: new Abstract: Long-horizon LLM agents increasingly rely on external execution support to maintain state, track progress, invoke tools, verify outcomes, and reuse experience across interactions.
arXiv Machine Learning
Aug 7
Predicting Task Difficulty Without Rollouts
arXiv:2608. 05797v1 Announce Type: new Abstract: Task difficulty dictates an agent's likelihood of success, and estimating it without rollouts means forecasting this directly from a task description before executing costly simulations in stateful environments.
Hugging Face Trending Papers
Aug 7
The Optimizer Is the Agent: Reasoning-Driven Search across Prompts, Programs, and ML Workflows
Recent systems for optimizing prompts, programs, and ML workflows typically rely on explicit outer-loop controllers such as evolutionary search, bandits, or textual-gradient methods. We ask a fundamentally different question: how much of this search policy can be internalized by a single tool-using agent?
Hugging Face Trending Papers
Aug 6
CalibForge: Adversarial Solver Calibration for Scaling Learnable Terminal Tasks
Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning. Executable validation establishes feasibility, yet does not reveal how a task behaves relative to a given solver setting.