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🔬 RESEARCH
"Keyword-matching benchmarks can credit small models for tool use they never perform. We document such a false positive in a matched-architecture pair of Spanish security language models and propose a ladder of strict, cheap diagnostics. A 661.6M parameter model (approx. 65% code/technical text; no d..."
🔬 RESEARCH
via Arxiv
👤 Zhe Zhou, Tianhua Tao
📅 2026-10-02
⚡ Score: 6.8
"Post-training with verifiable rewards can induce reward hacking, motivating the use of monitors within the training objective rather than solely for offline auditing. We show that a low monitor readout does not identify whether such an intervention controls behavior. In a code-generation environment..."
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🔬 RESEARCH
via Arxiv
👤 Lyuxin David Zhang, Eric Wong, Surbhi Goel et al.
📅 2026-10-02
⚡ Score: 6.8
"The choice of post-training data for large language models substantially affects downstream performance. Gradient-based data selection is a popular approach that ranks training data by how well their gradients align with those of a small validation set. However, ranking with full-parameter gradients..."
🔬 RESEARCH
via Arxiv
👤 Yu Li, Guangfeng Cai, Long-Fei Li et al.
📅 2026-10-02
⚡ Score: 6.8
"Terminal-using agents benefit from reinforcement learning (RL) in coding, debugging, and other multi-step terminal tasks. In these tasks, later commands often depend on information or intermediate results produced by earlier commands. However, existing trajectory-level and step-level credit assignme..."
🔬 RESEARCH
via Arxiv
👤 Hui Chen, Xuan Qi, James Xu Zhao et al.
📅 2026-10-02
⚡ Score: 6.7
"LLM-guided evolutionary methods, such as AlphaEvolve, have emerged as powerful approaches for challenging computational optimization problems, such as circle packing. However, prior work typically optimizes performance gain over a fixed number of iterations. We argue that practical optimization shou..."
🔬 RESEARCH
via Arxiv
👤 Lijie Ding, Changwoo Do
📅 2026-10-02
⚡ Score: 6.7
"Designing a scientific instrument tests whether language-model agents can do physics rather than recall it, provided the grading cannot be argued with. We introduce NeutronGym, to our knowledge the first executable environment for neutron instrument design: agents build instruments through validatin..."
🔬 RESEARCH
via Arxiv
👤 Gabriel Tomitsuka, Arman Raayatsanati, Emma Xing et al.
📅 2026-10-01
⚡ Score: 6.7
"Real-world enterprise data science and analytics workflows require reasoning across dozens of tables, performing statistical analyses, and acting on the results. Established text-to-SQL benchmarks evaluate query generation alone, and audits have found their answer keys frequently wrong. Because real..."
🔬 RESEARCH
via Arxiv
👤 Lucheng Fu, Kejing Xia, Yiyang Wang et al.
📅 2026-10-01
⚡ Score: 6.7
"Large language model (LLM) agents increasingly rely on persistent external sources to solve sequences of knowledge-intensive tasks. Existing methods improve how source content is accessed and organized, while agent-memory systems preserve reusable knowledge from prior interactions, but repeated use..."
🔬 RESEARCH
via Arxiv
👤 Pengfei Li, Naufal Suryanto, Sicheng Zhang et al.
📅 2026-10-01
⚡ Score: 6.7
"LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts' intent into tool invocations. However, existing evaluations focus on knowledge-based assessments or end-to-end agentic tasks, and do not directly measure LLMs' ability to generate executable comm..."
🔬 RESEARCH
"Policy-gradient methods are central to modern reinforcement learning, including LLM post-training. When they struggle, the usual suspects are exploration, credit assignment and action-sampling noise. Classification has none of them. A classifier is a policy whose expected reward, its \emph{expected..."
🔬 RESEARCH
via Arxiv
👤 Shuo Xing, Zilin Dai, Chengyuan Qian et al.
📅 2026-10-01
⚡ Score: 6.6
"While Large Language Models (LLMs) have demonstrated striking capabilities on frontier mathematical problems, it remains unclear whether they possess the structural mathematical understanding underlying their solutions. In this paper, we take a first step toward systematically studying mathematical..."
🔬 RESEARCH
via Arxiv
👤 Qiushi Han, Keya Hu, Linlu Qiu et al.
📅 2026-10-01
⚡ Score: 6.5
"We show that multimodal models possess strong reasoning abilities and that an appropriate harness can unlock their potential to solve tasks across diverse interactive environments. We introduce VISTA, a visual harness that gives a general-purpose multimodal model long-horizon vision. VISTA allows th..."
🔬 RESEARCH
via Arxiv
👤 Xuan Zhang, Longtao Zheng, Cunxiao Du et al.
📅 2026-10-01
⚡ Score: 6.4
"Coding agents solve repository-level software engineering tasks through long trajectories of code inspection, search, editing, and testing. As a task progresses, earlier exploration becomes stale, so managing context is more than avoiding overflow: an agent must decide when to compact, what working..."
🔬 RESEARCH
via Arxiv
👤 Hanchu Zhou, Dechen Gao, Hang Wang et al.
📅 2026-10-01
⚡ Score: 6.3
"Vision-language models (VLMs) and vision-language-action models (VLAs) have recently driven rapid progress in general-purpose robots, yet most progress has focused on single-robot settings. Extending these capabilities to multi-robot systems remains challenging because robots must coordinate long-ho..."
🔬 RESEARCH
via Arxiv
👤 Adithya Bhaskar, Jeffrey Cheng, Danqi Chen
📅 2026-10-02
⚡ Score: 6.1
"Modern chess engines are silent experts: they play at a superhuman level, but do not offer explanations for their play. On the other hand, language models (LMs) can generate plausible-sounding explanations, but their weak playing strength limits the utility of their explanations. We introduce Queen,..."
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