1 citations · 3 across the 20 of their papers we have counts for
26 papers
Information-Gain Calibrated On-Policy Distillation for Deep Search Agents
Chenxi Li, Xueyang Feng, Songyang Liu +4
On-policy distillation (OPD) has recently emerged as a promising approach for transferring the capabilities of large agents to compact students. In deep search, where agents iterat…
AgentSafeEvo: Adversarial Co-Evolution for LLM Agent Safety
Chenxu Wang, Xiaoyu Wen, Han Qi +4
Large language model (LLM) agents accomplish complex tasks through multi-turn interactions with external tools. However, malicious content embedded in user queries, tool descriptio…
Distilling Agentic Systems: A Roadmap across Models, Artifacts, and Harnesses
Ziluowen Luo, Senzhang Wang, Chaozhuo Li +9
Modern agents increasingly rely on memories, tools, and execution logic, so their competence extends beyond model parameters. This shift exposes a limitation of conventional knowle…
When Updating Stops Being Learning: Rethinking LLM Self-Evolution via learnable information gain
Chenxu Wang, Chaozhuo Li, Xinze Shi +6
Self-evolution lets large language models (LLMs) improve iteratively using their own generated data, but often suffers from self-evolution degeneration: performance improves, plate…
JailbreakSkill: Scaling Automated Red-Teaming with Reusable and Ever-Evolving Skills
Xiaoyu Wen, Jiajia Li, Zhida He +11
Automated red-teaming has produced a growing collection of attack strategies, yet they typically remain scattered across prompts and workflows, making them difficult to systematica…
Knowledge-Intensive Video Generation
Chenxu Wang, Mingda Chen
Text-to-video generation has advanced rapidly in visual quality, but remains under-evaluated for factuality and practical usefulness. We introduce knowledge-intensive video generat…
Design First, Code Later: Aesthetically Pleasing Template-Free Slides Generation
Zhiyao Cui, Chenxu Wang, Shuyue Hu +4
Producing presentation slides automatically entails coordinating narrative structure with page-level graphic design under strict spatial constraints. For such structured multimodal…
PRBench: End-to-end Paper Reproduction in Physics Research
Shi Qiu, Junyi Deng, Yiwei Deng +48
AI agents powered by large language models exhibit strong reasoning and problem-solving capabilities, enabling them to assist scientific research tasks such as formula derivation a…
ClawKeeper: Comprehensive Safety Protection for OpenClaw Agents Through Skills, Plugins, and Watchers
Songyang Liu, Chaozhuo Li, Chenxu Wang +8
OpenClaw has rapidly established itself as a leading open-source autonomous agent runtime, offering powerful capabilities including tool integration, local file access, and shell c…
The Devil Behind Moltbook: Anthropic Safety is Always Vanishing in Self-Evolving AI Societies
Chenxu Wang, Chaozhuo Li, Songyang Liu +10
The emergence of multi-agent systems built from large language models (LLMs) offers a promising paradigm for scalable collective intelligence and self-evolution. Ideally, such syst…
LLMRouterBench: A Massive Benchmark and Unified Framework for LLM Routing
Hao Li, Yiqun Zhang, Zhaoyan Guo +9
Large language model (LLM) routing assigns each query to the most suitable model from an ensemble. We introduce LLMRouterBench, a large-scale benchmark and unified framework for LL…
How Real is Your Jailbreak? Fine-grained Jailbreak Evaluation with Anchored Reference
Songyang Liu, Chaozhuo Li, Rui Pu +5
Jailbreak attacks present a significant challenge to the safety of Large Language Models (LLMs), yet current automated evaluation methods largely rely on coarse classifications tha…
LANCET: Neural Intervention via Structural Entropy for Mitigating Faithfulness Hallucinations in LLMs
Chenxu Wang, Chaozhuo Li, Pengbo Wang +7
Large Language Models have revolutionized information processing, yet their reliability is severely compromised by faithfulness hallucinations. While current approaches attempt to…
ICL-Router: In-Context Learned Model Representations for LLM Routing
Chenxu Wang, Hao Li, Yiqun Zhang +6
Large language models (LLMs) often exhibit complementary strengths. Model routing harnesses these strengths by dynamically directing each query to the most suitable model, given a…
Learning Compact Representations of LLM Abilities via Item Response Theory
Jianhao Chen, Chenxu Wang, Gengrui Zhang +5
Recent years have witnessed a surge in the number of large language models (LLMs), yet efficiently managing and utilizing these vast resources remains a significant challenge. In t…
PerPilot: Personalizing VLM-based Mobile Agents via Memory and Exploration
Xin Wang, Zhiyao Cui, Hao Li +10
Vision language model (VLM)-based mobile agents show great potential for assisting users in performing instruction-driven tasks. However, these agents typically struggle with perso…
Continual Gradient Low-Rank Projection Fine-Tuning for LLMs
Chenxu Wang, Yilin Lyu, Zicheng Sun +1
Continual fine-tuning of Large Language Models (LLMs) is hampered by the trade-off between efficiency and expressiveness. Low-Rank Adaptation (LoRA) offers efficiency but constrain…
Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation
Chenxu Wang, Yonggang Jin, Cheng Hu +7
Adapting a single agent to a new multi-agent system brings challenges, necessitating adjustments across various tasks, environments, and interactions with unknown teammates and opp…
The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants
Yiqun Zhang, Hao Li, Chenxu Wang +11
Proprietary giants are increasingly dominating the race for ever-larger language models. Can open-source, smaller models remain competitive across a broad range of tasks? In this p…
Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models
Chaozhuo Li, Pengbo Wang, Chenxu Wang +7
Edgar Allan Poe noted, "Truth often lurks in the shadow of error," highlighting the deep complexity intrinsic to the interplay between truth and falsehood, notably under conditions…
One SPACE to Rule Them All: Jointly Mitigating Factuality and Faithfulness Hallucinations in LLMs
Pengbo Wang, Chaozhuo Li, Chenxu Wang +3
LLMs have demonstrated unprecedented capabilities in natural language processing, yet their practical deployment remains hindered by persistent factuality and faithfulness hallucin…
Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading Comprehension
Chenxu Wang, Ping Jian, Zhen Yang
Logical reading comprehension is a challenging task that entails grasping the underlying semantics of text and applying reasoning to deduce the correct answer. Prior researches hav…
YZS-model: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention
Chenxu Wang, Haowei Ming, Jian He +2
Accurate prediction of drug molecule solubility is crucial for therapeutic effectiveness and safety. Traditional methods often miss complex molecular structures, leading to inaccur…
Prompt-based Logical Semantics Enhancement for Implicit Discourse Relation Recognition
Chenxu Wang, Ping Jian, Mu Huang
Implicit Discourse Relation Recognition (IDRR), which infers discourse relations without the help of explicit connectives, is still a crucial and challenging task for discourse par…