4 citations · 8 across the 31 of their papers we have counts for
14 papers · 1 filter
RuleTrek: Benchmarking Agentic Rule Reasoning in Complex Scenarios
Chenhao Yuan, Bohan Yu, Yinhao Xu +10
Large language models (LLMs) increasingly tackle complex real-world tasks in specialized domains. However, identifying and correctly applying domain-specific rules remains challeng…
Atria Dawn: The Dawn of Agentic Superintelligence
Honglin Guo, Tao Gui, Yicheng Chen +139
As AI agents become participants in the development of their successors, they reshape both the production of intelligence and the role of human researchers. We introduce Atria Dawn…
SAEScientist-Bench: Can AI Agents Conduct Autonomous SAE Interpretability Research?
Yuqiao Tan, Shizhu He, Jun Zhao +1
While research on recursive self-improvement (RSI) has predominantly automated model training pipelines, reliable autonomous development demands a missing pillar: post-hoc monitori…
SWE-Touch: Benchmarking Coding Agents When Users Touch the Code
Yuqiao Tan, Jinxiang Meng, Fangyu Lei +4
Real-world software development requires coding agents to operate in shared workspaces where users may inspect and modify code during an ongoing task, yet existing repository-level…
MemTools: A Unified Research Framework for Interoperable Agent Memory
Chengfeng Zhao, Jinhui Chen, Sirui Liang +4
While memory systems are essential for agent architectures, pervasive architectural fragmentation restricts systematic research. Existing implementations typically couple different…
Trace-Based On-Policy Distillation for Masked Diffusion Language Models
Haolin Ren, Ziyang Huang, Chenhao Yuan +2
Diffusion large language models (dLLMs) are a promising alternative to autoregressive generation. However, reasoning-oriented post-training for dLLMs remains challenging. Supervise…
Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steering
Chengfeng Zhao, Yuqiao Tan, Shizhu He +3
While Large Language Models (LLMs) excel as static solvers, transforming them into autonomous agents remains challenging. This transition requires continuous environmental interact…
SkillPyramid: A Hierarchical Skill Consolidation Framework for Self-Evolving Agents
Yuan Xiong, Ziqi Miao, Qian Chen +6
Recent AI agents can flexibly invoke skills to solve complex tasks, but their long-term improvement is fundamentally constrained by a lack of systematic skill construction, accumul…
SC-Taxo: Hierarchical Taxonomy Generation under Semantic Consistency Constraints using Large Language Models
Shiqiang Cai, Nianhong Niu, Shizhu He +2
Scientific literature is expanding at an unprecedented pace, making it increasingly challenging to efficiently organize and access domain knowledge. A high-quality scientific taxon…
DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios
Jinxiang Meng, Shaoping Huang, Fangyu Lei +17
Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benchmarks often suffer from cod…
From to : Investigating Reinforcement Learning in Pre-train Space
Yuqiao Tan, Minzheng Wang, Bo Liu +5
While reinforcement learning with verifiable rewards (RLVR) significantly enhances LLM reasoning by optimizing the conditional distribution P(y|x), its potential is fundamentally b…
ResAdapt: Adaptive Resolution for Efficient Multimodal Reasoning
Huanxuan Liao, Zhongtao Jiang, Yupu Hao +6
Multimodal Large Language Models (MLLMs) achieve stronger visual understanding by scaling input fidelity, yet the resulting visual token growth makes jointly sustaining high spatia…
GraphWalker: Agentic Knowledge Graph Question Answering via Synthetic Trajectory Curriculum
Shuwen Xu, Yao Xu, Jiaxiang Liu +4
Agentic knowledge graph question answering (KGQA) requires an agent to iteratively interact with knowledge graphs (KGs), posing challenges in both training data scarcity and reason…
WideSeek: Advancing Wide Research via Multi-Agent Scaling
Ziyang Huang, Haolin Ren, Xiaowei Yuan +6
Search intelligence is evolving from Deep Research to Wide Research, a paradigm essential for retrieving and synthesizing comprehensive information under complex constraints in par…