4 citations · 16 across the 29 of their papers we have counts for
8 papers · 1 filter
GraphMind: Interactive Novelty Assessment System for Accelerating Scientific Discovery
Italo Luis da Silva, Hanqi Yan, Lin Gui +1
Large Language Models (LLMs) show strong reasoning and text generation capabilities, prompting their use in scientific literature analysis, including novelty assessment. While eval…
When Thinking Backfires: Mechanistic Insights Into Reasoning-Induced Misalignment
Hanqi Yan, Hainiu Xu, Siya Qi +2
With the growing accessibility and wide adoption of large language models, concerns about their safety and alignment with human values have become paramount. In this paper, we iden…
Beyond Perplexity: Let the Reader Select Retrieval Summaries via Spectrum Projection Score
Zhanghao Hu, Qinglin Zhu, Siya Qi +3
Large Language Models (LLMs) have shown improved generation performance through retrieval-augmented generation (RAG) following the retriever-reader paradigm, which supplements mode…
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
Qinglin Zhu, Runcong Zhao, Hanqi Yan +3
Large Language Models (LLMs) struggle with complex reasoning due to limited diversity and inefficient search. We propose Soft Reasoning, an embedding-based search framework that op…
SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers
Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang +2
This study evaluates large language models (LLMs) in generating code from algorithm descriptions in recent NLP papers. The task requires two key competencies: (1) algorithm compreh…
Beyond Prompting: An Efficient Embedding Framework for Open-Domain Question Answering
Zhanghao Hu, Hanqi Yan, Qinglin Zhu +3
Large language models have recently pushed open domain question answering (ODQA) to new frontiers. However, prevailing retriever-reader pipelines often depend on multiple rounds of…
CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation
Zhenyi Shen, Hanqi Yan, Linhai Zhang +3
Chain-of-Thought (CoT) reasoning enhances Large Language Models (LLMs) by encouraging step-by-step reasoning in natural language. However, leveraging a latent continuous space for…
Beyond Cross-Modal Alignment: Measuring and Leveraging Modality Gap in Vision-Language Models
Hanqi Yan, Xiangxiang Cui, Lu Yin +4
The success of vision-language models is primarily attributed to effective alignment across modalities such as vision and language. However, modality gaps persist in existing align…