Papers by Jingwei Zhu

4 papers
On the Vulnerability of Safety Alignment in Open-Access LLMs (2024.findings-acl)

Copied to clipboard

Challenge: Large language models (LLMs) are susceptible to malicious exploitation, but are often rejected and limited harmfulness is limited.
Approach: They propose two types of reverse alignment techniques: reverse supervised fine-tuning (RSFT) and reverse preference optimization (RPO).
Outcome: The proposed methods can significantly enhance the success rate and harmfulness of jailbreak attacks, but they face high rejection rates and limited harmfulness.
CPsyExam: A Chinese Benchmark for Evaluating Psychology using Examinations (2025.coling-main)

Copied to clipboard

Challenge: CPsyExam prioritizes psychological knowledge and case analysis separately, recognizing the significance of applying psychological knowledge to real-world scenarios.
Approach: They propose a psychological benchmark, CPsyExam, constructed from questions from Chinese examination systems.
Outcome: The proposed benchmark prioritizes psychological knowledge and case analysis separately, recognizing the significance of applying psychological knowledge to real-world scenarios.
CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling (2024.findings-acl)

Copied to clipboard

Challenge: Existing datasets lack consulting knowledge, resulting in LLMs lacking professional consulting competence.
Approach: They propose a report-based multi-turn dialogue reconstruction framework for Chinese psychological counseling that uses large language models to assist counseling.
Outcome: The proposed framework is open-source and can be used in future research.
Hey, That’s My Data! Token-Only Dataset Inference in Large Language Models (2026.findings-acl)

Copied to clipboard

Challenge: Existing dataset inference methods require logit access, but many modern LLMs restrict such access.
Approach: They propose a token-only dataset inference framework that allows models to overwrite prior knowledge when trained on new data.
Outcome: The proposed framework overwrites prior knowledge when trained on new data.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations