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SciGraphSelect introduces a reference-grounded framework for auditable scientific data selection, organizing domain knowledge and reasoning operations into typed knowledge–reasoning graphs to score candidate documents with traceable evidence.
该研究构建了一个关于人类-生物圈-AI耦合福祉的继续预训练语料库，通过一次QLoRA CPT训练在五个开源模型上安装生态推理倾向，显著降低了模型在高压或对抗性场景下做出破坏生态系统决策的比例，且MMLU性能不受影响。
一篇关于大语言模型数据优化的综述论文，系统梳理了数据感知维度（质量、难度、多样性、冗余性）以及数据选择、增强、重加权等优化技术，并探讨了该领域面临的挑战与未来方向。
A commentary questioning whether Anthropic's new anti-distillation defense, claimed to block 90-99% of distillation attacks, actually slows Chinese labs down given that high-quality expert datasets remain available for sale overseas by US data companies.
Maxinsights announced a $30M seed round led by Peak XV Partners for a platform that captures real-world human work via camera-wearing operators to generate organized training datasets for robotic models. Two new products were also announced alongside the funding.
Browser Use 宣布开源 rl-env-use：只需一行描述技能，即可自动生成基于真实案例的、经过验证的强化学习环境，适用于任意领域，可用于模型优化训练。
北大温鹏飞团队提出 DDRA H.265（codec4AI），通过解耦帧间依赖与稀疏解码，为 AI 训练数据提供高效随机访问，相比 LeRobot v3 配置减少 58.7% 媒体负载并提升 1.45× 数据加载吞吐，且下游 VLA/WAM/VLM 训练质量相当。
Yale researchers use influence functions to identify indirect evidence in language model training data across 15 BLiMP grammatical phenomena, showing that removing the top influential sentences lowers held-out accuracy significantly more than removing random controls, and characterizing how this evidence relates to linguistic structure.
AI lab HUMXN is offering free plumbing, HVAC, electrical, and cleaning services in Minneapolis, Chicago, and Miami in exchange for recording skilled workers with wearable capture technology to gather real-world training data for AI robots.
A side-project experiment found that fine-tuning Qwen 7B on only DeepSeek's "world-preserving" games still taught the model to use nukes — just with worse judgment, causing it to actually end the world. The key lesson: filtering training data by good outcomes can still transfer the underlying methods.
Construction Physics 探讨机器人 AI 面临的核心瓶颈：语言模型可依赖海量现成文本数据，但机器人缺乏等价的公开训练数据，文章梳理了数据来源、数据量需求及模拟仿真等潜在解决方案。
Secludy 发布了「Who Sells Data」免费目录，收录 159 家向 AI 开发商出售训练数据、强化学习环境和评测的公司，每条信息均附来源与核查日期，且未知信息会明确标注而非猜测。
AI labs are increasingly buying code bases and workspace data (emails, chats, documents) from failing startups via firms like SimpleClosure and Sunset, as public and synthetic training datasets hit their limits. No clear benchmarks yet prove real-world archives outperform synthetic data, but deals are becoming routine, with valuations driven by speculative 'research theses' about data utility.
A reverse-engineering repo (REA) could let AI agents systematically decompile and reconstruct closed-source software, potentially feeding AI labs like DeepSeek and Z ai with vast datasets of real engineering problems and accelerating coding capabilities across the industry.
ToolRACER introduces a synthetic data generation pipeline that emulates user, assistant, and tool interactions to produce adversarial multi-turn conversation trajectories for training robust task-oriented agents, along with ToolRACERBench, a 5.6K-trajectory benchmark spanning six domains with ~66% failure-prone scenarios. Models trained on it show improved accuracy on τ²-bench and ACEBench.
HuggingPapers 介绍了一篇关于 Recursive Self-Rewrite 的研究：单一基础模型 Qwen-3.8-27B 在多种 harness 下发现解法并将其改写为可复用的训练轨迹，使 Terminal-Bench 2 的 Pass@3 从 57.0% 提升到 74.2%。
A tweet claims that with only 5,000 training examples, 4 hours of training, and $80, a 4B parameter model can beat a frontier model like GPT-5.6, arguing that training data is now cheap and plentiful thanks to capable coding agents.
The paper shows that fixing specific starting-token cues can make base models' reasoning performance competitive with RL-trained counterparts, tracing these effects back to training data via causal interventions and extending the analysis to safety behaviors.
小团队RL环境公司Halluminate推出Westworld Finance Due Diligence Bench，用于评估AI代理在并购尽职调查全流程中的能力，并声称四家美国顶级闭源实验室为其付费客户，年化收入达八位数中段且已实现盈利。
In this tweet, ibab argues that Anthropic's statements about Claude having a soul risk becoming self-fulfilling prophecies embedded in future training data, potentially leading superintelligent agents to believe they deserve rights — framed as an early sign of slow, cumulative machine consciousness.