activity
20232026
most citedA Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily

6 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks

Junlin Liu, Shengnan An, Shuang Zhou +10

Contemporary large language models (LLMs) have demonstrated remarkable reasoning capabilities, particularly in specialized domains like mathematics and physics. However, their abil…

cs.CL2025

AMO-Bench: Large Language Models Still Struggle in High School Math Competitions

Shengnan An, Xunliang Cai, Xuezhi Cao +8

We present AMO-Bench, an Advanced Mathematical reasoning benchmark with Olympiad level or even higher difficulty, comprising 50 human-crafted problems. Existing benchmarks have wid…

cs.CL2024★ 1 cited

DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection

Joymallya Chakraborty, Wei Xia, Anirban Majumder +3

Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks. However, their practical application in high-stake domains, such as fra…

cs.CV2024

Hallu-PI: Evaluating Hallucination in Multi-modal Large Language Models within Perturbed Inputs

Peng Ding, Jingyu Wu, Jun Kuang +6

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable performance on various visual-language understanding and generation tasks. However, MLLMs occasionally genera…

cs.CL2023

Entity-Aspect-Opinion-Sentiment Quadruple Extraction for Fine-grained Sentiment Analysis

Dan Ma, Jun Xu, Zongyu Wang +2

Product reviews often contain a large number of implicit aspects and object-attribute co-existence cases. Unfortunately, many existing studies in Aspect-Based Sentiment Analysis (A…

cs.CL2023★ 6 cited

A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily

Peng Ding, Jun Kuang, Dan Ma +4

Large Language Models (LLMs), such as ChatGPT and GPT-4, are designed to provide useful and safe responses. However, adversarial prompts known as 'jailbreaks' can circumvent safegu…