53 citations · 243 across the 107 of their papers we have counts for
16 papers · 1 filter
Correcting What You Cannot See: Credit Assignment for Perception Distillation in Multimodal Reasoners
Feng Xiong, Leyan Xue, Hongyu Lin
On-policy distillation provides dense supervision for multimodal reasoners, but its trajectory-level reward cannot determine whether a failed answer arose from perception or subseq…
DocOps: A Verifiable Benchmark for Autonomous Agents in Complex Document Operations
Jiazhen Jiang, Boxi Cao, Lingyong Yan +6
As autonomous agents rapidly evolve, their ability to reliably manipulate ubiquitous digital documents has become critical for enabling general-purpose AI assistants and automating…
MIRAGE: Mobile Agents with Implicit Reasoning and Generative World Models
Zhichao Yang, Yuanze Hu, Haojie Hao +7
Mobile agents are increasingly expected to operate everyday applications from screenshots and language goals, where reliable control requires reasoning over screen affordances, mul…
The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?
Xinyu Lu, Tianshu Wang, Pengbo Wang +8
Current AI benchmarks evaluate agents on task execution within human-designed workflows. These evaluations fundamentally fail to measure a critical next-level capability: whether m…
Beyond Text-Dominance: Understanding Modality Preference of Omni-modal Large Language Models
Xinru Yan, Boxi Cao, Yaojie Lu +4
Native Omni-modal Large Language Models (OLLMs) have shifted from pipeline architectures to unified representation spaces. However, this native integration gives rise to a critical…
SCA: Segment-Wise CoT Compression with Answer Alignment
Ye Tian, Hongyu Lin
Chain-of-thought (CoT) reasoning improves problem solving, but long think traces increase inference cost. Existing CoT compression methods usually optimize completion-level length.…
DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation
Hao Zheng, Guozhao Mo, Xinru Yan +7
Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing presentation agents often rely on p…
When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models
Yingzhi Mao, Chunkang Zhang, Junxiang Wang +6
Large Reasoning Models (LRMs) achieve strong performance on complex multi-step reasoning, yet they still exhibit severe safety failures such as harmful content generation. Existing…
LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?
Guozhao Mo, Wenliang Zhong, Jiawei Chen +7
Model Context Protocol (MCP) has become a key infrastructure for connecting LLMs with external tools, scaling to 10,000+ MCP servers with diverse tools. Unfortunately, there is sti…
ARise: Towards Knowledge-Augmented Reasoning via Risk-Adaptive Search
Yize Zhang, Tianshu Wang, Sirui Chen +6
Large language models (LLMs) have demonstrated impressive capabilities and are receiving increasing attention to enhance their reasoning through scaling test--time compute. However…
DeepSolution: Boosting Complex Engineering Solution Design via Tree-based Exploration and Bi-point Thinking
Zhuoqun Li, Haiyang Yu, Xuanang Chen +6
Designing solutions for complex engineering challenges is crucial in human production activities. However, previous research in the retrieval-augmented generation (RAG) field has n…
PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides
Hao Zheng, Xinyan Guan, Hao Kong +7
Automatically generating presentations from documents is a challenging task that requires accommodating content quality, visual appeal, and structural coherence. Existing methods p…
DeepRAG: Thinking to Retrieve Step by Step for Large Language Models
Xinyan Guan, Jiali Zeng, Fandong Meng +6
Large Language Models (LLMs) have shown remarkable reasoning capabilities, while their practical applications are limited by severe factual hallucinations due to limitations in the…
Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering
Xinyan Guan, Yanjiang Liu, Xinyu Lu +8
The evolution of machine learning has increasingly prioritized the development of powerful models and more scalable supervision signals. However, the emergence of foundation models…
DOMAINEVAL: An Auto-Constructed Benchmark for Multi-Domain Code Generation
Qiming Zhu, Jialun Cao, Yaojie Lu +4
Code benchmarks such as HumanEval are widely adopted to evaluate the capabilities of Large Language Models (LLMs), providing insights into their strengths and weaknesses. However,…
CRUXEval-X: A Benchmark for Multilingual Code Reasoning, Understanding and Execution
Ruiyang Xu, Jialun Cao, Yaojie Lu +6
Code benchmarks such as HumanEval are widely adopted to evaluate Large Language Models' (LLMs) coding capabilities. However, there is an unignorable programming language bias in ex…