1 citations · 3 across the 20 of their papers we have counts for
13 papers · 1 filter
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…