Diagnostic Tree

InquiTree: Evaluating AI Agents in the Scientific Inquiry Loop with Paper-Derived Research Trees

Announce Type: new Abstract: While LLM-based agents are increasingly used in scientific workflows, it remains unclear whether they are truly qualified for the dynamic and uncertain process of discovery. Existing static evaluations often conflate genuine reasoning with rote memorization. We introduce InquiTree, a diagnostic environment that formalizes scientific inquiry as interactive Research Trees: directed acyclic graphs capturing the logical dependencies among hypothesis formulation,...

Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards

Announce Type: new Abstract: Reinforcement learning has recently shown promise in improving large language models for Text-to-SQL generation, yet existing methods typically optimize one-shot rewards defined over a single SQL state. Such rewards provide limited guidance for iterative SQL correction and are insufficient to capture the improvement of multi-turn SQL refinement. In this paper, we propose Progress-SQL, a multi-turn reinforcement learning framework with progressive rewards for...

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection

arXiv:2606.08146v1 Announce Type: new Abstract: Fraud detection in payment, e-commerce, and telecommunications systems requires accuracy at the individual level, robustness under severe class imbalance, and ease of understanding for risk managers. Existing methods fall at least one of these requirements: automated machine learning systems search a fixed numerical space without semantic awareness of the dataset; graph neural network-based methods require pre-defined relational graphs and...

ANDES: Agent Native Data Evolving Synthesis Tool for Autonomous Instruction Alignment

arXiv:2606.01279v1 Announce Type: new Abstract: AI agents are increasingly being tasked with automating AI research itself, particularly the critical post-training phase that transforms base LLMs into aligned assistants. However, recent evaluations reveal that even frontier agents struggle to perform this task. While the success of post-training fundamentally relies on acquiring high-quality data, relying on agents to autonomously curate targeted training datasets from the open web...

Port React Compiler to Rust

[compiler] Port React Compiler to Rust#36173 This is an experimental, work-in-progress port of React Compiler to Rust. Key points: - Work-in-progress - we are sharing early, prior to testing internally at Meta, to get feedback from partners in parallel with continued development.

Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models

Announce Type: new Abstract: Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining useful life in engineered assets. These tasks are central to maintenance planning, but industrial PHM data are often fragmented, partially observed, and poorly labeled, which hinders supervised learning. Foundation models offer a route toward reusable predictive systems, yet most time-series foundation models are...

Revisiting Model Stitching In the Foundation Model Era

arXiv:2603.12433v3 Announce Type: replace Abstract: Model stitching, connecting early layers of one model (source) to later layers of another (target) via a light stitch layer, has served as a probe of representational compatibility. Prior work finds that models trained on the same dataset remain stitchable (negligible accuracy drop) despite different initializations or objectives. We revisit stitching for Vision Foundation Models (VFMs) that vary in objectives, data, and modality mix (e.g.,...

Medieval pandemic left a hidden legacy in Europe's oldest trees

Medieval pandemic left a hidden legacy in Europe's oldest trees Lisa Lock Scientific Editor Andrew Zinin Lead Editor A new study published in the Proceedings of the National Academy of Sciences demonstrates how radiocarbon dating can reveal the maximum lifespan of Mediterranean hardwoods, uncovering hidden links between human history and long-term ecosystem dynamics. By analyzing mature and ancient oak trees across Italy, researchers found that a millennium of age is attainable from the...

Beyond AI as Assistants: Toward Autonomous Discovery in Cosmology

arXiv:2605.14791v2 Announce Type: replace-cross Abstract: Recent advances in artificial intelligence (AI) agents are pushing AI beyond tools toward autonomous scientific discovery. We discuss two complementary agentic systems for cosmology: \texttt{CMBEvolve}, which targets tasks with explicit quantitative objectives through LLM-guided code evolution and tree search, and \texttt{CosmoEvolve}, which targets open-ended scientific workflows through a virtual multi-agent research laboratory. As...

Malware dev tries to steal Claude users' secrets, writes npm slop, leaks own GitHub private token