5 papers
Glasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents
Cong Pang, Jiaqi Su, Chengrui Wu +13
Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source agents remains challenging…
Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search
Ping Liu, Qianqi Shen, Jianqiang Shen +11
Job-search platforms rely on low-bandwidth query interfaces that often fail to capture the high-dimensional complexity of candidate profiles. We present an end-to-end RLAIF (Reinfo…
A Unified Structured Query Understanding Framework for Industrial Semantic Search
Ping Liu, Qianqi Shen, Jianqiang Shen +15
Query understanding in large-scale industrial search systems is typically implemented as a cascade of disparate, task-specific components. While individually optimizable, this frag…
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning
Zedong Wang, Siyuan Li, Dan Xu
Despite the promise of Multi-Task Learning in leveraging complementary knowledge across tasks, existing multi-task optimization (MTO) techniques remain fixated on resolving conflic…
Taming LLMs by Scaling Learning Rates with Gradient Grouping
Siyuan Li, Juanxi Tian, Zedong Wang +4
Training large language models (LLMs) poses challenges due to their massive scale and heterogeneous architectures. While adaptive optimizers like AdamW help address gradient variat…