202 citations · 558 across the 43 of their papers we have counts for
11 papers · 1 filter
CycleResearcher: Improving Automated Research via Automated Review
Yixuan Weng, Minjun Zhu, Guangsheng Bao +4
The automation of scientific discovery has been a long-standing goal within the research community, driven by the potential to accelerate knowledge creation. While significant prog…
Locking Down the Finetuned LLMs Safety
Minjun Zhu, Linyi Yang, Yifan Wei +2
Fine-tuning large language models (LLMs) on additional datasets is often necessary to optimize them for specific downstream tasks. However, existing safety alignment measures, whic…
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models
Jun Wang, Meng Fang, Ziyu Wan +10
In this technical report, we introduce OpenR, an open-source framework designed to integrate key components for enhancing the reasoning capabilities of large language models (LLMs)…
Personality Alignment of Large Language Models
Minjun Zhu, Yixuan Weng, Linyi Yang +1
Aligning large language models (LLMs) typically aim to reflect general human values and behaviors, but they often fail to capture the unique characteristics and preferences of indi…
A Rationale-centric Counterfactual Data Augmentation Method for Cross-Document Event Coreference Resolution
Bowen Ding, Qingkai Min, Shengkun Ma +3
Based on Pre-trained Language Models (PLMs), event coreference resolution (ECR) systems have demonstrated outstanding performance in clustering coreferential events across document…
CulturePark: Boosting Cross-cultural Understanding in Large Language Models
Cheng Li, Damien Teney, Linyi Yang +3
Cultural bias is pervasive in many large language models (LLMs), largely due to the deficiency of data representative of different cultures. Typically, cultural datasets and benchm…
Detoxifying Large Language Models via Knowledge Editing
Mengru Wang, Ningyu Zhang, Ziwen Xu +7
This paper investigates using knowledge editing techniques to detoxify Large Language Models (LLMs). We construct a benchmark, SafeEdit, which covers nine unsafe categories with va…
GenDec: A robust generative Question-decomposition method for Multi-hop reasoning
Jian Wu, Linyi Yang, Yuliang Ji +3
Multi-hop QA (MHQA) involves step-by-step reasoning to answer complex questions and find multiple relevant supporting facts. However, Existing large language models'(LLMs) reasonin…
Human Simulacra: Benchmarking the Personification of Large Language Models
Qiuejie Xie, Qiming Feng, Tianqi Zhang +7
Large language models (LLMs) are recognized as systems that closely mimic aspects of human intelligence. This capability has attracted attention from the social science community,…
How Likely Do LLMs with CoT Mimic Human Reasoning?
Guangsheng Bao, Hongbo Zhang, Cunxiang Wang +2
Chain-of-thought emerges as a promising technique for eliciting reasoning capabilities from Large Language Models (LLMs). However, it does not always improve task performance or ac…
Cofca: A Step-Wise Counterfactual Multi-hop QA benchmark
Jian Wu, Linyi Yang, Zhen Wang +2
While Large Language Models (LLMs) excel in question-answering (QA) tasks, their real reasoning abilities on multiple evidence retrieval and integration on Multi-hop QA tasks remai…