SchGen introduces a semantic-grounded code model for PCB schematic generation, achieving 82% valid circuits with 60.5% functional correctness from natural language prompts.

Qinpei Luo, Ruichun Ma, Xinyu Zhang et al.

Proposed VisAnomReasoner fine-tuned on VisAnomBench achieves 74.30% precision and 72.17% F1 in time-series anomaly detection, surpassing baselines by over 21 and 23 points.

Xiaona Zhou, Muntasir Wahed, Tianjiao Yu et al.

A multi-agent system with semantic communication and checkpoints enhances adaptive method selection.

Geremy Loachamín-Suntaxi, Robert Lazar, Dimitrios G. Giovanis et al.

Quantifying and optimizing simplicity via polynomial representations enhances generalization in image and text classification.

Tianren Zhang, Xiangxin Li, Minghao Xiao et al.

LFQ method enhances low-bit quantized LLMs' generation quality by minimizing cross-entropy in the final block.

Jung Hyun Lee, June Yong Yang, Jungwook Choi et al.

UI-KOBE enhances lightweight GUI agents with app-specific graph knowledge, boosting task success rate to 77.6%.

Yuxiang Chai, Han Xiao, Xinyu Fu et al.

DistractionIF reveals inverse scaling in large models under distractor instructions; GRPO improves robustness by 15.5%.

Zeli Su, Zhankai Xu, Tianlei Chen et al.

BenchTrace evaluates LLM reflection and controlled evolution using 1821 annotated failure episodes, introducing FAR as a key metric.

Jiahao Huang, Fei Cheng, Junfeng Jiang et al.

Proposes Calibrated Collective Oversight (CCO), integrating multiple auxiliary signals with Conformal Decision Theory for online calibration, ensuring AI behavior aligns with safety targets.

William Overman, Mohsen Bayati

CubePart: An open-vocabulary, part-controllable 3D generator for semantic structure generation.

Yiheng Zhu, Kangle Deng, Jean-Philippe Fauconnier et al.

CORE algorithm enables rapid reasoning improvement using fewer samples and rollouts through contrastive reflection.

Linas Nasvytis, Simon Jerome Han, Ben Prystawski et al.

LiveBrowseComp shows that search agents often verify memory: on 335 fresh-fact questions, closed-book accuracy stayed below 2%.

HuiMing Fan, Xiao Wang, Zheng Chu et al.

Woodpecker Distillation uses weak models to diagnose and correct local reasoning bugs, improving mathematical reasoning accuracy by 1.4% on average.

Dayu Wang, Jiaye Yang, Weikang Li et al.

This study analyzes how sample difficulty influences RLVR, revealing medium difficulty samples yield the strongest and most stable reasoning improvements.

Yue Cheng, Jiajun Zhang, Xiaohui Gao et al.

AIBuildAI-2 uses hierarchical knowledge system to automate AI model building, achieving 70.7% medal rate.

Ruiyi Zhang, Peijia Qin, Qi Cao et al.

MUSE-Autoskill improves task success to 68.4% via unified skill lifecycle management and cross-agent skill transfer.

Huawei Lin, Peng Li, Jie Song et al.

BRANE uses LLM-extracted query features to dynamically optimize retrieval configurations, achieving up to 89% cost savings on MuSiQue and others.

Melissa Z. Pan, Negar Arabzadeh, Mathew Jacob et al.

Anchor formalizes enterprise workflows via constraint programming, mitigating artifact drift and enabling controlled task generation with certified solutions.

Maksim Ivanov, Abhijay Rana

AgingBench evaluates long-lived AI agents via four mechanisms, enabling diagnosis and targeted repair to sustain reliability.

Jianing Zhu, Yeonju Ro, John Robertson et al.

FEP-Diff achieves cognitively plausible trajectory prediction under partial observability using the Free Energy Principle.

Yanping Wu, Ji Zhang, Hao Chen et al.