19 citations · 22 across the 5 of their papers we have counts for
5 papers
WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning
Zhepei Wei, Wenlin Yao, Yao Liu +9
While reinforcement learning (RL) has demonstrated remarkable success in enhancing large language models (LLMs), it has primarily focused on single-turn tasks such as solving math…
Improving Tool Retrieval by Leveraging Large Language Models for Query Generation
Mohammad Kachuee, Sarthak Ahuja, Vaibhav Kumar +2
Using tools by Large Language Models (LLMs) is a promising avenue to extend their reach beyond language or conversational settings. The number of tools can scale to thousands as th…
Open World Classification with Adaptive Negative Samples
Ke Bai, Guoyin Wang, Jiwei Li +5
Open world classification is a task in natural language processing with key practical relevance and impact. Since the open or {\em unknown} category data only manifests in the infe…
Ranking-Enhanced Unsupervised Sentence Representation Learning
Yeon Seonwoo, Guoyin Wang, Changmin Seo +6
Unsupervised sentence representation learning has progressed through contrastive learning and data augmentation methods such as dropout masking. Despite this progress, sentence enc…
An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking
Puyang Xu, Qi Hu
We highlight a practical yet rarely discussed problem in dialogue state tracking (DST), namely handling unknown slot values. Previous approaches generally assume predefined candida…