17 papers
Training Documents Reranker with Search Rubrics for Deep Research Agent
Wenhan Liu, Yu Lu, Qiaolin Xia +8
Retrieval systems help deep research agents generate high-quality answers by providing relevant documents. However, existing retrievers typically select documents through relevance…
Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models
Hao Wang, Hao Gu, Hongming Piao +6
The paper introduces CurioSFT, an entropy-preserving supervised fine-tuning approach that uses adaptive self-distillation to keep exploration abilities in large reasoning models, l…
SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection
Zhiyong Cao, Dunqiang Liu, Qi Dai +9
Task-oriented proactive dialogue agents play a pivotal role in recruitment, particularly for steering conversations towards specific business outcomes, such as acquiring social-med…
AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model
Changze Lv, Jiang Zhou, Siyu Long +22
We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, encompassing pretraining scaling laws,…
SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs
Hao Wang, Jialun Zhong, Changcheng Wang +5
Knowledge-based conversational question answering (KBCQA) confronts persistent challenges in resolving coreference, modeling contextual dependencies, and executing complex logical…
FOREVER: Forgetting Curve-Inspired Memory Replay for Language Model Continual Learning
Yujie Feng, Hao Wang, Jian Li +6
Continual learning (CL) for large language models (LLMs) aims to enable sequential knowledge acquisition without catastrophic forgetting. Memory replay methods are widely used for…