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Wanli Li, Bowen Zhou, Yunyao Yu +4 authors
WeaveBench presents a comprehensive benchmark for evaluating computer-use agents across multiple interfaces, revealing significant challenges in long-horizon task orchestration and highlighting the limitations of traditional performance assessment methods.
Lei Bai, Zongsheng Cao, Yang Chen +47 authors
Agents-A1, a 35B Mixture-of-Experts Agentic Model, achieves trillion-parameter-level performance through long-horizon trajectory scaling and heterogeneous agent ability scaling via a three-stage training approach involving supervised fine-tuning, domain-level teacher models, and multi-teacher distillation.
Maksim Savkin, Mikhail Goncharov, Alexander Gambashidze +7 authors
Compact task-specialized language models demonstrate superior performance in multi-hop reasoning and faithfulness compared to larger general-purpose models through a novel training pipeline and structured reasoning traces.
Wanghan Xu, Shuo Li, Tianlin Ye +47 authors
ResearchClawBench evaluates autonomous scientific research capabilities across 40 tasks from 10 domains using expert-curated criteria and reveals current limitations in re-discovery accuracy among AI agents and LLMs.
Songhao Wu, Zhongxin Chen, Yuxuan Liu +3 authors
Text embeddings from large language models are enhanced by EmbedFilter, a linear transformation that reduces the influence of high-frequency tokens and improves semantic representations while enabling dimensionality reduction.
Jiayu Liu, Qihan Lin, Cheng Qian +8 authors
PlanBench-XL evaluates large language model agents' ability to plan and adapt in complex tool-rich environments with limited visibility and dynamic disruptions.
Jiacheng Chen, Xinyu Zhang, Shunkai Zhang +20 authors
MaxProof is a test-time scaling framework that enhances mathematical proof generation by combining multiple proof-oriented capabilities and using population-level search with tournament selection to achieve competitive performance on high-level mathematical competitions.
Shaoqiu Zhang, Maoquan Wang, Yuling Shi +5 authors
FastContext separates repository exploration from code solving in LLM agents using specialized exploration models that reduce token consumption and improve resolution rates.
Liliana Hotsko, Yinxi Li, Yuntian Deng +1 authors
Code2LoRA is a hypernetwork framework that generates repository-specific LoRA adapters for code language models, supporting both static and evolving codebases with efficient parameter-efficient fine-tuning.
Songhao Wu, Ang Lv, Ruobing Xie +1 authors
Researchers propose a novel router redesign for Mixture-of-Experts models that aligns router rows with the principal singular directions of expert matrices using Manifold Power Iteration to improve model effectiveness.
Ang Li, Ben Liu, Bin Han +215 authors
Ling-2.6 and Ring-2.6 models are presented as scalable solutions for agentic intelligence, featuring architectural upgrades and specialized training methods to balance fast response times with advanced reasoning capabilities.
Youyang Yin, Huanhuan Liu, YY +14 authors
Unlimited OCR introduces Reference Sliding Window Attention to eliminate growing memory consumption during long-sequence OCR tasks, enabling efficient transcription of multiple pages in a single forward pass.
Dian Zheng, Harry Lee, Manyuan Zhang +4 authors
InterleaveThinker enables interleaved generation capabilities for image generators through a multi-agent pipeline with planner and critic agents, achieving performance comparable to state-of-the-art models while enhancing reasoning benchmarks.
Wei Zhou, Xiongwei Zhu, Zelin Xu +8 authors
A novel on-policy generative field distillation framework called DanceOPD is proposed to unify text-to-image generation, local editing, and global editing capabilities in flow-matching models through capability-specific routing and velocity-based training.
Xinyu Wang, Chongbo Zhao, Fangneng Zhan +1 authors
A novel streaming video editing framework enables causal, frame-by-frame editing with stable long-horizon preservation and real-time responsiveness through a three-stage distillation pipeline and AR-oriented mask cache.
Jiaqi Tang, Jianmin Chen, Youyang Zhai +6 authors
Robust-U1 enhances multimodal large language models' robustness against visual corruptions through self-recovery capabilities that improve both visual quality and reasoning performance.
Jincheng Zhong, Weizhi Wang, Che Jiang +5 authors
EnterpriseClawBench presents a benchmark for enterprise agents based on real-world sessions with 852 reproducible tasks, emphasizing comprehensive evaluation metrics beyond single performance scores.
Vishesh Tripathi, Abhay Kumar
Grouped Query Experts (GQE) improves Transformer efficiency by selectively activating query heads based on token content while maintaining key-value cache benefits of grouped-query attention.
Fukang Wen, Zhijie Wang, Ruilin Xu
OpenRath introduces a PyTorch-like programming model for multi-agent systems using Session as a central runtime abstraction that enables explicit fork, merge, and replay operations while recording comprehensive execution state.
Yifu Luo, Zeyu Chen, Haoyu Wang +4 authors
d-OPSD introduces a novel on-policy self-distillation framework for diffusion language models by adapting self-teacher construction and supervision mechanisms to match the non-autoregressive nature of diffusion models.
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