5 citations · 17 across the 11 of their papers we have counts for
11 papers
Retrieval-Augmented Visual Question Answering via Built-in Autoregressive Search Engines
Xinwei Long, Zhiyuan Ma, Ermo Hua +3
Retrieval-augmented generation (RAG) has emerged to address the knowledge-intensive visual question answering (VQA) task. Current methods mainly employ separate retrieval and gener…
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Runze Liu, Junqi Gao, Jian Zhao +5
Test-Time Scaling (TTS) is an important method for improving the performance of Large Language Models (LLMs) by using additional computation during the inference phase. However, cu…
Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization
Biqing Qi, Zhouyi Qian, Yiang Luo +4
As multi-modal large language models (MLLMs) are increasingly applied to complex reasoning tasks, the diversity and quality of reasoning paths become crucial factors affecting thei…
Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation
Biqing Qi, Kaiyan Zhang, Kai Tian +6
The rapid growth of biomedical knowledge has outpaced our ability to efficiently extract insights and generate novel hypotheses. Large language models (LLMs) have emerged as a prom…
Towards Building Specialized Generalist AI with System 1 and System 2 Fusion
Kaiyan Zhang, Biqing Qi, Bowen Zhou
In this perspective paper, we introduce the concept of Specialized Generalist Artificial Intelligence (SGAI or simply SGI) as a crucial milestone toward Artificial General Intellig…
Online DPO: Online Direct Preference Optimization with Fast-Slow Chasing
Biqing Qi, Pengfei Li, Fangyuan Li +3
Direct Preference Optimization (DPO) improves the alignment of large language models (LLMs) with human values by training directly on human preference datasets, eliminating the nee…