24 citations · 55 across the 5 of their papers we have counts for
5 papers
Debate, Reflect, and Distill: Multi-Agent Feedback with Tree-Structured Preference Optimization for Efficient Language Model Enhancement
Xiaofeng Zhou, Heyan Huang, Lizi Liao
Large Language Models (LLMs) continue to set new standards in knowledge-intensive and complex reasoning tasks, yet their high computational demands limit widespread adoption. While…
SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
Shuai Zhao, Heyan Huang, Xinge Li +2
Neural networks have demonstrated exceptional performance in supervised learning, benefiting from abundant high-quality annotated data. However, obtaining such data in real-world s…
ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training
Le Zhuo, Zewen Chi, Minghao Xu +5
We propose ProtLLM, a versatile cross-modal large language model (LLM) for both protein-centric and protein-language tasks. ProtLLM features a unique dynamic protein mounting mecha…
On the Representation Collapse of Sparse Mixture of Experts
Zewen Chi, Li Dong, Shaohan Huang +9
Sparse mixture of experts provides larger model capacity while requiring a constant computational overhead. It employs the routing mechanism to distribute input tokens to the best-…
XLM-E: Cross-lingual Language Model Pre-training via ELECTRA
Zewen Chi, Shaohan Huang, Li Dong +8
In this paper, we introduce ELECTRA-style tasks to cross-lingual language model pre-training. Specifically, we present two pre-training tasks, namely multilingual replaced token de…