12 citations · 28 across the 23 of their papers we have counts for
10 papers · 1 filter
Controlling Performance and Budget of a Centralized Multi-agent LLM System with Reinforcement Learning
Bowen Jin, TJ Collins, Donghan Yu +10
Large language models (LLMs) exhibit complementary strengths across domains and come with varying inference costs, motivating the design of multi-agent LLM systems where specialize…
An Empirical Study on Reinforcement Learning for Reasoning-Search Interleaved LLM Agents
Bowen Jin, Jinsung Yoon, Priyanka Kargupta +2
Reinforcement learning (RL) has demonstrated strong potential in training large language models (LLMs) capable of complex reasoning for real-world problem solving. More recently, R…
Hypercube-Based Retrieval-Augmented Generation for Scientific Question-Answering
Jimeng Shi, Sizhe Zhou, Bowen Jin +5
Large language models (LLMs) often need to incorporate external knowledge to solve theme-specific problems. Retrieval-augmented generation (RAG) has shown its high promise, empower…
Hybrid Latent Reasoning via Reinforcement Learning
Zhenrui Yue, Bowen Jin, Huimin Zeng +6
Recent advances in large language models (LLMs) have introduced latent reasoning as a promising alternative to autoregressive reasoning. By performing internal computation with hid…
CoRank: LLM-Based Compact Reranking with Document Features for Scientific Retrieval
Runchu Tian, Xueqiang Xu, Bowen Jin +2
Scientific retrieval is essential for advancing scientific knowledge discovery. Within this process, document reranking plays a critical role in refining first-stage retrieval resu…
GRAPHGPT-O: Synergistic Multimodal Comprehension and Generation on Graphs
Yi Fang, Bowen Jin, Jiacheng Shen +3
The rapid development of Multimodal Large Language Models (MLLMs) has enabled the integration of multiple modalities, including texts and images, within the large language model (L…
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Bowen Jin, Hansi Zeng, Zhenrui Yue +5
Efficiently acquiring external knowledge and up-to-date information is essential for effective reasoning and text generation in large language models (LLMs). Prompting advanced LLM…
Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation
SeongKu Kang, Bowen Jin, Wonbin Kweon +4
In specialized fields like the scientific domain, constructing large-scale human-annotated datasets poses a significant challenge due to the need for domain expertise. Recent metho…
LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin +5
Large Language Models (LLMs) have revolutionized artificial intelligence with capabilities in reasoning, coding, and communication, driving innovation across industries. Their true…
Deep Learning and Foundation Models for Weather Prediction: A Survey
Jimeng Shi, Azam Shirali, Bowen Jin +10
Physics-based numerical models have been the bedrock of atmospheric sciences for decades, offering robust solutions but often at the cost of significant computational resources. De…