34 citations · 44 across the 6 of their papers we have counts for
6 papers
CARE: An Explainable Computational Framework for Assessing Client-Perceived Therapeutic Alliance Using Large Language Models
Anqi Li, Chenxiao Wang, Yu Lu +3
Client perceptions of the therapeutic alliance are critical for counseling effectiveness. Accurately capturing these perceptions remains challenging, as traditional post-session qu…
Do Large Language Models Truly Grasp Addition? A Rule-Focused Diagnostic Using Two-Integer Arithmetic
Yang Yan, Yu Lu, Renjun Xu +1
Large language models (LLMs) achieve impressive results on advanced mathematics benchmarks but sometimes fail on basic arithmetic tasks, raising the question of whether they have t…
QUBE: Enhancing Automatic Heuristic Design via Quality-Uncertainty Balanced Evolution
Zijie Chen, Zhanchao Zhou, Yu Lu +3
Solving NP-hard problems traditionally relies on heuristics, yet manually designing effective heuristics for complex problems remains a significant challenge. While recent advancem…
Nova: An Iterative Planning and Search Approach to Enhance Novelty and Diversity of LLM Generated Ideas
Xiang Hu, Hongyu Fu, Jinge Wang +7
Scientific innovation is pivotal for humanity, and harnessing large language models (LLMs) to generate research ideas could transform discovery. However, existing LLMs often produc…
Unveiling the Impact of Multi-Modal Interactions on User Engagement: A Comprehensive Evaluation in AI-driven Conversations
Lichao Zhang, Jia Yu, Shuai Zhang +10
Large Language Models (LLMs) have significantly advanced user-bot interactions, enabling more complex and coherent dialogues. However, the prevalent text-only modality might not fu…
Scientific Large Language Models: A Survey on Biological & Chemical Domains
Qiang Zhang, Keyang Ding, Tianwen Lyv +22
Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelli…