15 citations · 79 across the 42 of their papers we have counts for
17 papers · 1 filter
Free Process Rewards without Process Labels
Lifan Yuan, Wendi Li, Huayu Chen +6
Different from its counterpart outcome reward models (ORMs), which evaluate the entire responses, a process reward model (PRM) scores a reasoning trajectory step by step, providing…
Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization
Ermo Hua, Che Jiang, Xingtai Lv +7
Extending the context length of Language Models (LMs) by improving Rotary Position Embedding (RoPE) has become a trend. While prior works mainly address RoPE's limitations within a…
How to Synthesize Text Data without Model Collapse?
Xuekai Zhu, Daixuan Cheng, Hengli Li +7
Model collapse in synthetic data indicates that iterative training on self-generated data leads to a gradual decline in performance. With the proliferation of AI models, synthetic…
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…
Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention
Xingtai Lv, Ning Ding, Kaiyan Zhang +3
Improving the effectiveness and efficiency of large language models (LLMs) simultaneously is a critical yet challenging research goal. In this paper, we find that low-rank pre-trai…
A Static and Dynamic Attention Framework for Multi Turn Dialogue Generation
Wei-Nan Zhang, Yiming Cui, Kaiyan Zhang +4
Recently, research on open domain dialogue systems have attracted extensive interests of academic and industrial researchers. The goal of an open domain dialogue system is to imita…
A Stack-Propagation Framework for Low-Resource Personalized Dialogue Generation
Haoyu Song, Wei-Nan Zhang, Kaiyan Zhang +1
With the resurgent interest in building open-domain dialogue systems, the dialogue generation task has attracted increasing attention over the past few years. This task is usually…
Efficient Diffusion Models: A Comprehensive Survey from Principles to Practices
Zhiyuan Ma, Yuzhu Zhang, Guoli Jia +7
As one of the most popular and sought-after generative models in the recent years, diffusion models have sparked the interests of many researchers and steadily shown excellent adva…
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…
SMR: State Memory Replay for Long Sequence Modeling
Biqing Qi, Junqi Gao, Kaiyan Zhang +4
Despite the promising performance of state space models (SSMs) in long sequence modeling, limitations still exist. Advanced SSMs like S5 and S6 (Mamba) in addressing non-uniform sa…
Fast and Slow Generating: An Empirical Study on Large and Small Language Models Collaborative Decoding
Kaiyan Zhang, Jianyu Wang, Ning Ding +4
Large Language Models (LLMs) exhibit impressive capabilities across various applications but encounter substantial challenges such as high inference latency, considerable training…
UltraMedical: Building Specialized Generalists in Biomedicine
Kaiyan Zhang, Sihang Zeng, Ermo Hua +11
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains and are moving towards more specialized areas. Recent advanced proprietary models such…
Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process
Ermo Hua, Biqing Qi, Kaiyan Zhang +4
Supervised Fine-Tuning (SFT) and Preference Optimization (PO) are key processes for aligning Language Models (LMs) with human preferences post pre-training. While SFT excels in eff…
CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following
Kaiyan Zhang, Jianyu Wang, Ermo Hua +3
With the advancement of language models (LMs), their exposure to private data is increasingly inevitable, and their deployment (especially for smaller ones) on personal devices, su…
Generative Multi-Modal Knowledge Retrieval with Large Language Models
Xinwei Long, Jiali Zeng, Fandong Meng +4
Knowledge retrieval with multi-modal queries plays a crucial role in supporting knowledge-intensive multi-modal applications. However, existing methods face challenges in terms of…