OpenAI Blog
Jul 9
ChatGPT is now a partner for your most ambitious work
ChatGPT Work is an agent that can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
Hugging Face Trending Papers
Jul 9
Multi-Agent Firewall Architecture for Privacy Protection of Sensitive Data in Interactions with Language Models
While Large Language Models (LLMs) have become essential productivity tools, their integration into workflows without adequate safeguards creates significant risks. This paper proposes an open-source, privacy-focused, user-facing firewall designed to secure both web-based and programmatic LLM interactions.
Hugging Face Trending Papers
Jul 9
LEEVLA: Seeing What Matters in Latent Environment Evolution for Vision-Language-Action
Vision-language-action (VLA) models aim to map multimodal inputs to robot actions. However, most existing approaches struggle to cover complex dynamic scenarios due to treating all visual tokens uniformly and reasoning with human-selected factors, which lack mechanisms to emphasize task-critical evidence and ignore underlying factors.
Hugging Face Trending Papers
Jul 9
CausalDS: Benchmarking Causal Reasoning in Data-Science Agents
Large language models (LLMs) increasingly act as integrated data-science agents, combining abstract reasoning with advanced tool use. Yet the relevant benchmark landscape largely divides into symbolic causal reasoning benchmarks without realistic data analysis or data analysis benchmarks without a principled causal data-generating structure.
arXiv Machine Learning
Jul 9
Safe Reinforcement Learning using Ideas from Model Predictive Control
arXiv:2607. 07252v1 Announce Type: new Abstract: Reinforcement learning (RL) enables the synthesis of control policies directly from data, making it highly appealing for complex cyber-physical systems (CPSs) and robotics.
arXiv AI
Jul 9
LLM-powered reasoning in agent-based modeling
arXiv:2607. 06757v1 Announce Type: new Abstract: Agent-based modeling (ABM) has the capability to model millions of individuals and their interactions, which is useful for policy making.
arXiv AI
Jul 9
Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production
arXiv:2607. 07052v1 Announce Type: cross Abstract: AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously solved problems.
arXiv AI
Jul 9
HiDVFS: Hierarchical Multi-Agent DVFS for Real-Time OpenMP DAG Workloads
arXiv:2601. 06425v2 Announce Type: replace-cross Abstract: Leakage power in multicore embedded systems now rivals dynamic power, so DVFS schedulers must respect deadlines and thermal limits, not just average makespan.
arXiv AI
Jul 9
The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents
arXiv:2607. 07436v1 Announce Type: new Abstract: A self-evolving agent retires its bad skills by watching them fail, so what happens when the judge cannot see the failures?
arXiv AI
Jul 9
AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org
arXiv:2512. 11935v2 Announce Type: replace Abstract: Agentic AI systems increasingly connect large language models (LLMs) to external scientific tools, yet whether and when tool access improves prediction accuracy remains uncharacterized.
arXiv Machine Learning
Jul 9
TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
arXiv:2605. 15207v2 Announce Type: replace Abstract: Multi-agent LLM systems have shown promise for complex reasoning, yet recent evaluations reveal they often underperform single-model baselines.
arXiv AI
Jul 9
SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents
arXiv:2607. 07676v1 Announce Type: new Abstract: Autonomous AI agents can execute complex tasks with limited human review, yet they often lack the grounded operational knowledge to make their outputs not just executable but correct, secure, and maintainable.
arXiv AI
Jul 9
Institutional Red-Teaming: Deployment Rules, Not Just Models, Causally Shape Multi-Agent AI Safety
arXiv:2607. 07695v1 Announce Type: new Abstract: We introduce institutional red-teaming, an evaluation methodology for testing deployment rules in multi-agent AI: hold the agents, objectives, and task state fixed, vary only one rule, and attribute the resulting change in collective behavior to that rule.
arXiv AI
Jul 9
Evaluating SageMath-Augmented LLM Agents for Computational and Experimental Mathematics
arXiv:2607. 06820v1 Announce Type: new Abstract: Recent advances in AI for Mathematics have focused largely on autoformalization and theorem proving, leaving the role of Computer Algebra Systems (CAS) in agentic LLM workflows underexplored.
arXiv AI
Jul 9
Agon: Competitive Cross-Model RL with Implicit Rival Grading of Reasoning
arXiv:2607. 07690v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards (e.
arXiv AI
Jul 9
STAGformer: A Spatio-temporal Agent Graph Transformer for Micro Mobility Demand Forecasting
arXiv:2607. 06614v1 Announce Type: cross Abstract: Accurate station-level demand forecasting is essential for the efficient operation of bike-sharing systems, yet it remains challenging due to complex spatio-temporal dependencies and the large scale of urban networks.
arXiv AI
Jul 9
Measuring Intelligence Beyond Human Scale
arXiv:2607. 07040v1 Announce Type: new Abstract: How can we measure intelligence beyond human capability?
arXiv AI
Jul 9
Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass
arXiv:2607. 07696v1 Announce Type: cross Abstract: Analytical workloads operating on data stored in external database systems face a fundamental bottleneck: data access is guarded entirely by the database driver, like JDBC or ODBC, forcing all reads through query execution and other driver layers that are not designed for bulk columnar analytics.
arXiv AI
Jul 9
Effective Strategies for Asynchronous Software Engineering Agents
arXiv:2603. 21489v2 Announce Type: replace-cross Abstract: AI agents have become increasingly capable at isolated software engineering (SWE) tasks such as resolving issues on Github.
arXiv AI
Jul 9
Towards Agentic AI Governance: A Preliminary Assessment
arXiv:2607. 07612v1 Announce Type: cross Abstract: Artificial intelligence is rapidly evolving from generative systems to agentic AI capable of autonomously planning and executing tasks.