3 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
In-Context Editing: Learning Knowledge from Self-Induced Distributions
Siyuan Qi, Bangcheng Yang, Kailin Jiang +5
In scenarios where language models must incorporate new information efficiently without extensive retraining, traditional fine-tuning methods are prone to overfitting, degraded gen…
Panacea: Pareto Alignment via Preference Adaptation for LLMs
Yifan Zhong, Chengdong Ma, Xiaoyuan Zhang +5
Current methods for large language model alignment typically use scalar human preference labels. However, this convention tends to oversimplify the multi-dimensional and heterogene…
ValueDCG: Measuring Comprehensive Human Value Understanding Ability of Language Models
Zhaowei Zhang, Fengshuo Bai, Jun Gao +1
Personal values are a crucial factor behind human decision-making. Considering that Large Language Models (LLMs) have been shown to impact human decisions significantly, it is esse…
Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games
Chengdong Ma, Ziran Yang, Hai Ci +4
The primary challenge in deploying Large Language Model (LLM) is ensuring its harmlessness. Red team can identify vulnerabilities by attacking LLM to attain safety. However, curren…