paper.dinq.meAI 与前沿科学顶会 · 学术新星雷达
登录 DINQ
返回新星榜
CL

Chaochao Lu

ACL 2026×3AAAI 2026×2ICLR 2026×2推理对齐与偏好安全强化学习与后训练评测与基准
新星分资深
38
一作贡献0
核心/参与27
方向广度16
合作网络12
0 一作 · 7 篇 · ACL 2026 / AAAI 2026 / ICLR 2026

获取完整研究档案

首次获取该候选人的完整档案及 StartLux 评估共 20 积分;每位用户单独解锁,之后查看免费。主动刷新 20 积分。

联系方式

实时查找电子邮箱,费用不超过20积分;未找到邮箱不扣费。

2026 顶会论文

7
作者位次 #3/3ACL 2026Findings· Findings of ACL

Can Post-Training Transform LLM s into Causal Reasoners?

Junqi Chen · Sirui Chen · Chaochao Lu

摘要

Causal inference is essential for decision-making but remains challenging for non-experts. While large language models (LLMs) show promise in this domain, their precise causal estimation capabilities are still limited, and the impact of post-training on these abilities is insufficiently explored....

强化学习与后训练评测与基准推理OpenReview 项目页
作者位次 #10/10ACL 2026Findings· Findings of ACL

Evolving Agentic Workflow Driven by Human-Agent Collaboration

Yuxin Liu · Jinxuan Zhang · Yuezhang Peng · Hefeng Zhou · Xiangfeng Wang · Jiong Lou · Chentao Wu · Jie Li · Jingjing Qu · Chaochao Lu

摘要

Agentic workflows, composed of multiple collaborating Large Language Models (LLMs), have become a key paradigm for complex problem-solving. However, their effectiveness is often hindered by three critical challenges: high manual design costs, inefficient agentic search, and poor dynamic adaptabil...

对齐与偏好检索与知识推理OpenReview 项目页
作者位次 #5/6ACL 2026Findings· Findings of ACL

Adaptive Prompt Optimization for Open-Ended Tasks: Uncertainty Preference as a Secondary Signal

Shuyang Zhang · Zhixuan Liu · Zhichen Dong · Hao Zhang · Chaochao Lu · Chao Yang

摘要

Prompt optimizers are widely used to create high-quality prompts for Large Language Models (LLMs), but their effectiveness remains unstable in practice. This instability is caused by the misalignment between conservative needs (e.g., safety compliance) and open-ended goals (e.g., creative writing...

对齐与偏好安全评测与基准OpenReview 项目页
作者位次 #2/3AAAI 2026Poster· Artificial Intelligence

SHADOW: Dynamic-Aware Credit Assignment Against Long-Horizon Tasks

Yuze Liu · Chaochao Lu · Chao Yang

常见合作者