arXiv AI
Jul 17
Provable Coordination for LLM Agents via Message Sequence Charts
arXiv:2604. 17612v3 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are difficult to reason about.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv Machine Learning
Jul 17
Augmentations for Robust and Efficient Imitation Learning in Streamed Video Games
arXiv:2607. 14200v1 Announce Type: new Abstract: Imitation learning is an appealing way to scale game-playing agents to complex 3D environments by training policies to map visual observations to actions from human demonstrations.
arXiv Machine Learning
Jul 17
LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget
arXiv:2607. 14952v1 Announce Type: new Abstract: A growing gap separates inference context lengths from RL post-training: inference systems are approaching million-token contexts, while post-training workloads often remain at 256K tokens or below and rely on length generalization at deployment.
arXiv AI
Jul 17
A framework for single and multi-agent human-AI curiosity ecosystems
arXiv:2607. 06214v2 Announce Type: replace Abstract: This paper offers a framework for considering curiosity as an ecosystem.
arXiv AI
Jul 17
Tactile: Giving Computer-Using Agents Hands and Feet
arXiv:2607. 14443v1 Announce Type: new Abstract: Computer-use agents are becoming capable software operators, but their interface to desktop applications is still often a brittle motor layer: they look at screenshots, predict coordinates, click, and hope that the visible state changed as intended.
arXiv AI
Jul 17
LQCDMaster: Agentic Scientific Computing for Lattice Quantum Chromodynamics Research
arXiv:2607. 15001v1 Announce Type: cross Abstract: Lattice quantum chromodynamics (LQCD) provides a first-principles framework for computing hadronic observables, but its practical use remains limited by the substantial expertise required to turn research motivation into reliable computing workflows.
arXiv AI
Jul 17
Automatic Hard Example Synthesis with Multi-Level Agentic Data Curation
arXiv:2607. 14256v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed for nuanced content safety and moderation tasks, yet they remain vulnerable to adversarial attacks and out-of-distribution edge cases.
arXiv AI
Jul 17
Semantic Audio-driven Understanding for Dynamic Humanoid Whole Body Control
arXiv:2607. 14182v1 Announce Type: cross Abstract: Recent advances in humanoid robotics and reinforcement learning have enabled the acquisition of highly expressive whole-body motion policies.
arXiv AI
Jul 17
Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving
arXiv:2607. 14387v1 Announce Type: new Abstract: Validating autonomous driving systems requires diverse, regulation-compliant test scenarios.
arXiv AI
Jul 17
Instant NuRec: Feed-Forward 3D Gaussian Reconstruction for Driving Scene Simulation
arXiv:2607. 14203v1 Announce Type: cross Abstract: 3D simulation platforms are critical for autonomous driving because they enable end-to-end policy evaluation, thereby reducing development costs and improving safety.
arXiv AI
Jul 17
VOiLA: Vectorized Online Planning with Learned Diffusion Models for POMDP Agents
arXiv:2606. 19729v2 Announce Type: replace-cross Abstract: Planning under uncertainty is an essential capability for autonomous robots.
arXiv AI
Jul 17
Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generation
arXiv:2607. 14165v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated significant capability in software code generation, their application to analog Electronic Design Automation (EDA) is bottlenecked.
arXiv Machine Learning
Jul 17
Governing Generative AI Across Financial Institutions: A Framework for Generative AI Risk Control
arXiv:2607. 04103v3 Announce Type: replace-cross Abstract: Generative artificial intelligence is moving from general-purpose experimentation toward specialized applications across banking, capital markets, insurance, payments, and wealth management.
arXiv AI
Jul 17
Bad Memory: Evaluating Prompt Injection Risks from Memory in Agentic Systems
arXiv:2607. 14611v1 Announce Type: cross Abstract: A growing class of agentic systems maintain persistent state across sessions through memory files, behavioral preferences, and knowledge bases.
arXiv AI
Jul 17
The Industrialization of Research ; On AI-Driven Science and Its Consequences
arXiv:2607. 15164v1 Announce Type: new Abstract: Artificial intelligence is transforming scientific research - not merely as a more powerful instrument, but as an autonomous participant in the research cycle itself.
arXiv AI
Jul 17
LOTAPO: Leave-One-Turn Attribution for Self-Generated Process Rewards in Multi-Turn Search Reasoning
arXiv:2607. 13501v2 Announce Type: replace Abstract: Reinforcement learning for multi-turn search reasoning typically relies on terminal outcome rewards, which cannot distinguish useful, redundant, and harmful intermediate interactions.
arXiv AI
Jul 17
ToolAlignBench: Investigating Alignment Conflicts in Tool-Calling Enabled LLMs
arXiv:2607. 14285v1 Announce Type: cross Abstract: Safety alignment in LLMs aims to align models with human values, but which values take precedence when they conflict?
arXiv AI
Jul 17
From Stateless to Situated: Building a Psychological World for LLM-Based Agents
arXiv:2603. 25031v2 Announce Type: replace Abstract: In psychological support and emotional companionship scenarios, the core limitation of large language models (LLMs) lies not merely in response quality, but in their reliance on local next-token prediction, which prevents them from maintaining the temporal continuity, stage awareness, and user consent boundaries required for multi-turn intervention.
arXiv AI
Jul 17
Traccia: An OpenTelemetry-Based Governance Platform for AI Systems
arXiv:2607. 14309v1 Announce Type: new Abstract: The rapid development of Large Language Models (LLMs) and Artificial Intelligent (AI) powered autonomous agents has fundamentally changed the existing forms of software governance.
arXiv AI
Jul 17
TopoAgent: A Self-Evolving Topological Agent for Multimodal Scientific Reasoning
arXiv:2607. 14658v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general tasks, rigorous scientific reasoning remains challenging due to the limitations of monolithic, linear planning.