13 citations · 23 across the 12 of their papers we have counts for
7 papers · 1 filter
CJEval: A Benchmark for Assessing Large Language Models Using Chinese Junior High School Exam Data
Qian-Wen Zhang, Haochen Wang, Fang Li +5
Online education platforms have significantly transformed the dissemination of educational resources by providing a dynamic and digital infrastructure. With the further enhancement…
Tell Me What You Don't Know: Enhancing Refusal Capabilities of Role-Playing Agents via Representation Space Analysis and Editing
Wenhao Liu, Siyu An, Junru Lu +8
Role-Playing Agents (RPAs) have shown remarkable performance in various applications, yet they often struggle to recognize and appropriately respond to hard queries that conflict w…
SNFinLLM: Systematic and Nuanced Financial Domain Adaptation of Chinese Large Language Models
Shujuan Zhao, Lingfeng Qiao, Kangyang Luo +3
Large language models (LLMs) have become powerful tools for advancing natural language processing applications in the financial industry. However, existing financial LLMs often fac…
VITA: Towards Open-Source Interactive Omni Multimodal LLM
Chaoyou Fu, Haojia Lin, Zuwei Long +16
The remarkable multimodal capabilities and interactive experience of GPT-4o underscore their necessity in practical applications, yet open-source models rarely excel in both areas.…
FinVerse: An Autonomous Agent System for Versatile Financial Analysis
Siyu An, Qin Li, Junru Lu +2
With the significant advancements in cognitive intelligence driven by LLMs, autonomous agent systems have attracted extensive attention. Despite this growing interest, the developm…
Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergence
Junru Lu, Jiazheng Li, Siyu An +4
Direct Preference Optimization (DPO) has emerged as a prominent algorithm for the direct and robust alignment of Large Language Models (LLMs) with human preferences, offering a mor…
FIPO: Free-form Instruction-oriented Prompt Optimization with Preference Dataset and Modular Fine-tuning Schema
Junru Lu, Siyu An, Min Zhang +3
When the quality of naive prompts is carefully optimized by human experts, the task performance of large language models (LLMs) can be significantly improved. However, expert-based…