40 papers
Socratic Skill Learning: Interleaving Teaching and Practice for Transferable Agent Skills
Letian Zhu, Han Li, Yifan Yao +9
Agent Skills improve LLM agents by making task knowledge reusable across sessions. Learning transferable Skills requires evidence about a procedure and its conditions of use, which…
ANCHOR: Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding
Wenqiang Zhu, Xinping Lei, Zhiyi Lai +17
For repository-grounded coding agents, a functionally correct patch is not necessarily an acceptable one: developers also constrain how the task must be carried out-modification sc…
GameLogicBench: Evaluating Coding Agents on Runtime Game Logic with Tick-Level State Assertions
Xinyu Che, Yunfei Ge, Shihao Li +9
Coding agents can modify and test code across large software projects. Game development is a domain where agents must implement gameplay rules. A game can end in a valid state even…
Procedura: Agentic 3D Modeling with Procedural Control
Youtian Lin, Yikang Yang, Zhanpeng Hu +5
Native 3D generators now recover impressive mesh geometry from a single image. However, a dense mesh stays soft where a machined object should be sharp, it carries no part decompos…
LoopsBench: From Harness Engineering to Loop Engineering in Coding Agent Evaluation
Han Li, Zhemin Fang, Rili Feng +8
Coding agent infrastructure is shifting from harness engineering toward loop engineering as coding agents are deployed for sustained long-horizon software development. Existing ben…
AVE-Compass: Towards Holistic Evaluation for Audio-Video Editing Abilities
Yuqing Wen, Yukai Huang, Qianqian Xie +6
While instruction-based video editing has advanced rapidly, real-world videos contain tightly coupled audio and visual signals, and editing one modality often requires coordinated…
ABot-AgentOS: A General Robotic Agent OS with Lifelong Multi-modal Memory
Jiayi Tian, Shiao Liu, Yuting Xu +30
Recent VLM and VLA systems have improved robotic perception and action prediction, yet long-horizon embodied agents still require a general runtime layer for reasoning, memory, too…
AVSCap: Orchestrating Audio-Visual Synergy for Omni-modal Video Captioning
Yanghai Wang, Jiahao Wang, Jiafu Tang +9
Omni-modal video captioning is not merely combining visual captioning with audio transcription: a useful caption must describe how visual actions, speech, music, and sound effects…
CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents
Zhanbo Hua, Yifan Yao, Weihao Xie +14
While recent LLM-based terminal agents have demonstrated promising capabilities, the scarcity of high-quality, executable training data remains a critical bottleneck. Existing synt…
TVIR: Building Deep Research Agents Towards Text-Visual Interleaved Report Generation
Xinkai Ma, Zhiqi Bai, Dingling Zhang +21
Deep Research Agents have shown strong capability in multi-step information retrieval, reasoning, and long-form report generation, but existing benchmarks and systems remain predom…
P3D-Bench: Benchmarking MLLMs for Parametric 3D Generation and Structural Reasoning
Yikang Yang, Zhanpeng Hu, Youtian Lin +5
Multimodal large language models can write code to produce complex programs as well as use programs to do 3D modeling, which opens up a new avenue for 3D generation powered by thei…
CoVEBench: Can Video Editing Models Handle Complex Instructions?
Jiangtao Wu, Jiaming Wang, Yiwen He +7
While recent text-guided video editing models excel at elementary tasks (e.g., style transfer, object insertion), real-world user requests are highly compositional. A single prompt…
AudioProcessBench: Benchmark for Identifying Process Errors in Audio-Grounded Reasoning
Xiangyu Zhao, Junyu Yan, Yaling Shen +7
Large audio-language models (LALMs) increasingly use explicit reasoning traces for complex audio understanding, yet the evaluation of reasoning quality remains underexplored. Altho…
OmniCap-IF: Benchmarking and Improving Instruction Following Abilities for Omni-Video Captioning
Jiahao Wang, An Ping, Yanghai Wang +13
While Omni-modal Large Language Models (OLLMs) have demonstrated impressive capabilities in jointly processing audio and visual streams, their ability to strictly adhere to complex…
Where Do Deep-Research Agents Go Wrong? Span-Level Error Localization in Agent Trajectories
Jiaming Wang, Ziteng Feng, Jiangtao Wu +8
Deep-research agents solve tasks through long trajectories of search, tool use, evidence inspection, and answer synthesis. Evaluation based on final answers shows whether an agent…
MMG2Skill: Can Agents Distill In-the-Wild Guides into Self-Evolving Skills?
Xinyu Che, Junqi Xiong, Yunfei Ge +9
Abundant procedural knowledge on the Web holds great potential for helping agents solve long-horizon tasks. However, such knowledge is often multimodal, heterogeneous, noisy, and i…
Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution
Han Li, Jinyu Tian, Rili Feng +10
Large language models (LLMs) still struggle with the rigorous reasoning demands of hard competitive programming. While recent multi-agent frameworks attempt to bridge this reliabil…
When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors
Chenghao Yang, Yuning Zhang, Zhoufutu Wen +4
Model distillation is a primary driver behind the rapid progress of LLM agents, yet it often leads to behavioral homogenization. Many emerging agents share nearly identical reasoni…
WebCompass: Towards Multimodal Web Coding Evaluation for Code Language Models
Xinping Lei, Xinyu Che, Junqi Xiong +16
Large language models are rapidly evolving into interactive coding agents capable of end-to-end web coding, yet existing benchmarks evaluate only narrow slices of this capability,…
Vibe AIGC: A New Paradigm for Content Generation via Agentic Orchestration
Jiaheng Liu, Yuanxing Zhang, Shihao Li +1
For the past decade, the trajectory of generative artificial intelligence (AI) has been dominated by a model-centric paradigm driven by scaling laws. Despite significant leaps in v…
OmniSIFT: Modality-Asymmetric Token Compression for Efficient Omni-modal Large Language Models
Yue Ding, Yiyan Ji, Jungang Li +12
Omni-modal Large Language Models (Omni-LLMs) have demonstrated strong capabilities in audio-video understanding tasks. However, their reliance on long multimodal token sequences le…
ViDiC: Video Difference Captioning
Jiangtao Wu, Shihao Li, Zhaozhou Bian +7
Understanding visual differences between dynamic scenes requires the comparative perception of compositional, spatial, and temporal changes--a capability that remains underexplored…
MVU-Eval: Towards Multi-Video Understanding Evaluation for Multimodal LLMs
Tianhao Peng, Haochen Wang, Yuanxing Zhang +13
The advent of Multimodal Large Language Models (MLLMs) has expanded AI capabilities to visual modalities, yet existing evaluation benchmarks remain limited to single-video understa…
SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models
Jingxuan Xu, Ken Deng, Weihao Li +36
Evaluating large language models (LLMs) for software engineering has been limited by narrow task coverage, language bias, and insufficient alignment with real-world developer workf…