3 citations · 8 across the 10 of their papers we have counts for
10 papers
ResLoRA: Identity Residual Mapping in Low-Rank Adaption
Shuhua Shi, Shaohan Huang, Minghui Song +7
As one of the most popular parameter-efficient fine-tuning (PEFT) methods, low-rank adaptation (LoRA) is commonly applied to fine-tune large language models (LLMs). However, updati…
HD-Eval: Aligning Large Language Model Evaluators Through Hierarchical Criteria Decomposition
Yuxuan Liu, Tianchi Yang, Shaohan Huang +6
Large language models (LLMs) have emerged as a promising alternative to expensive human evaluations. However, the alignment and coverage of LLM-based evaluations are often limited…
Text Diffusion with Reinforced Conditioning
Yuxuan Liu, Tianchi Yang, Shaohan Huang +6
Diffusion models have demonstrated exceptional capability in generating high-quality images, videos, and audio. Due to their adaptiveness in iterative refinement, they provide a st…
Improving Domain Adaptation through Extended-Text Reading Comprehension
Ting Jiang, Shaohan Huang, Shengyue Luo +8
To enhance the domain-specific capabilities of large language models, continued pre-training on a domain-specific corpus is a prevalent method. Recent work demonstrates that adapti…
Auto Search Indexer for End-to-End Document Retrieval
Tianchi Yang, Minghui Song, Zihan Zhang +4
Generative retrieval, which is a new advanced paradigm for document retrieval, has recently attracted research interests, since it encodes all documents into the model and directly…
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
Zhaoyang Wang, Shaohan Huang, Yuxuan Liu +8
Large language models (LLMs) exhibit impressive emergent abilities in natural language processing, but their democratization is hindered due to huge computation requirements and cl…