activity
20212026
most citedEvaluating Large Language Models Trained on Code

1.5k citations · 1.7k across the 20 of their papers we have counts for

collaborators
Showing 2025Show all

5 papers · 1 filter

cs.AI2025

ScheduleMe: Multi-Agent Calendar Assistant

Oshadha Wijerathne, Amandi Nimasha, Dushan Fernando +2

Recent advancements in LLMs have contributed to the rise of advanced conversational assistants that can assist with user needs through natural language conversation. This paper pre…

cs.CL2025

Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems

Shang-Chi Tsai, Yun-Nung Chen

With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…

cs.CL2025★ 5 cited

FinanceReasoning: Benchmarking Financial Numerical Reasoning More Credible, Comprehensive and Challenging

Zichen Tang, Haihong E, Ziyan Ma +10

We introduce FinanceReasoning, a novel benchmark designed to evaluate the reasoning capabilities of large reasoning models (LRMs) in financial numerical reasoning problems. Compare…

cs.CL2025

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning

Erxin Yu, Jing Li, Ming Liao +7

Although large language models demonstrate strong performance across various domains, they still struggle with numerous bad cases in mathematical reasoning. Previous approaches to…

cs.CL2025

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification

Yashwanth M., Vaibhav Singh, Ayush Maheshwari +2

We propose ARISE, a framework that iteratively induces rules and generates synthetic data for text classification. We combine synthetic data generation and automatic rule induction…