54 citations · 55 across the 4 of their papers we have counts for
4 papers
DeepDiver: Adaptive Search Intensity Scaling via Open-Web Reinforcement Learning
Wenxuan Shi, Haochen Tan, Chuqiao Kuang +7
Information seeking demands iterative evidence gathering and reflective reasoning, yet large language models (LLMs) still struggle with it in open-web question answering. Existing…
SELF: Self-Evolution with Language Feedback
Jianqiao Lu, Wanjun Zhong, Wenyong Huang +9
Large Language Models (LLMs) have demonstrated remarkable versatility across various domains. To further advance LLMs, we propose 'SELF' (Self-Evolution with Language Feedback), a…
Aligning Large Language Models with Human: A Survey
Yufei Wang, Wanjun Zhong, Liangyou Li +6
Large Language Models (LLMs) trained on extensive textual corpora have emerged as leading solutions for a broad array of Natural Language Processing (NLP) tasks. Despite their nota…
Neural Subgraph Isomorphism Counting
Xin Liu, Haojie Pan, Mutian He +3
In this paper, we study a new graph learning problem: learning to count subgraph isomorphisms. Different from other traditional graph learning problems such as node classification…