1.5k citations · 1.6k across the 10 of their papers we have counts for
11 papers
Unveiling Fine-Grained Visual Traces: Evaluating Multimodal Interleaved Reasoning Chains in Multimodal STEM Tasks
Jing Jin, Hao Liu, Yan Bai +9
Multimodal large language models (MLLMs) have shown promising reasoning abilities, yet evaluating their performance in specialized domains remains challenging. STEM reasoning is a…
Do Vision-Language Models Truly Perform Vision Reasoning? A Rigorous Study of the Modality Gap
Yige Xu, Yongjie Wang, Zizhuo Wu +3
Reasoning in vision-language models (VLMs) has recently attracted significant attention due to its broad applicability across diverse downstream tasks. However, it remains unclear…
SoftCoT++: Test-Time Scaling with Soft Chain-of-Thought Reasoning
Yige Xu, Xu Guo, Zhiwei Zeng +1
Test-Time Scaling (TTS) refers to approaches that improve reasoning performance by allocating extra computation during inference, without altering the model's parameters. While exi…
SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs
Yige Xu, Xu Guo, Zhiwei Zeng +1
Chain-of-Thought (CoT) reasoning enables Large Language Models (LLMs) to solve complex reasoning tasks by generating intermediate reasoning steps. However, most existing approaches…
RevMUX: Data Multiplexing with Reversible Adapters for Efficient LLM Batch Inference
Yige Xu, Xu Guo, Zhiwei Zeng +1
Large language models (LLMs) have brought a great breakthrough to the natural language processing (NLP) community, while leading the challenge of handling concurrent customer queri…
Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition
Yige Xu, Zhiwei Zeng, Zhiqi Shen
Emotion Recognition in Conversation (ERC) has been widely studied due to its importance in developing emotion-aware empathetic machines. The rise of pre-trained language models (PL…
One2Set: Generating Diverse Keyphrases as a Set
Jiacheng Ye, Tao Gui, Yichao Luo +2
Recently, the sequence-to-sequence models have made remarkable progress on the task of keyphrase generation (KG) by concatenating multiple keyphrases in a predefined order as a tar…
Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learning
Yichao Luo, Yige Xu, Jiacheng Ye +2
Aiming to generate a set of keyphrases, Keyphrase Generation (KG) is a classical task for capturing the central idea from a given document. Based on Seq2Seq models, the previous re…
Pre-trained Models for Natural Language Processing: A Survey
Xipeng Qiu, Tianxiang Sun, Yige Xu +3
Recently, the emergence of pre-trained models (PTMs) has brought natural language processing (NLP) to a new era. In this survey, we provide a comprehensive review of PTMs for NLP.…
Improving BERT Fine-Tuning via Self-Ensemble and Self-Distillation
Yige Xu, Xipeng Qiu, Ligao Zhou +1
Fine-tuning pre-trained language models like BERT has become an effective way in NLP and yields state-of-the-art results on many downstream tasks. Recent studies on adapting BERT t…
How to Fine-Tune BERT for Text Classification?
Chi Sun, Xipeng Qiu, Yige Xu +1
Language model pre-training has proven to be useful in learning universal language representations. As a state-of-the-art language model pre-training model, BERT (Bidirectional Enc…