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20232026
most citedCT-GAT: Cross-Task Generative Adversarial Attack based on Transferability

1 citations · 2 across the 6 of their papers we have counts for

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cs.CL2026

Mem2ActBench: A Benchmark for Evaluating Long-Term Memory Utilization in Task-Oriented Autonomous Agents

Yiting Shen, Kun Li, Wei Zhou +1

Large Language Model (LLM)-based agents are increasingly deployed for complex, tool-based tasks where long-term memory is critical to driving actions. Existing benchmarks, however,…

cs.CL2024

Fine-Grained Behavior Simulation with Role-Playing Large Language Model on Social Media

Kun Li, Chenwei Dai, Wei Zhou +1

Large language models (LLMs) have demonstrated impressive capabilities in role-playing tasks. However, there is limited research on whether LLMs can accurately simulate user behavi…

cs.CL2024

Improve Student's Reasoning Generalizability through Cascading Decomposed CoTs Distillation

Chengwei Dai, Kun Li, Wei Zhou +1

Large language models (LLMs) exhibit enhanced reasoning at larger scales, driving efforts to distill these capabilities into smaller models via teacher-student learning. Previous w…

cs.CL2024

Beyond Imitation: Learning Key Reasoning Steps from Dual Chain-of-Thoughts in Reasoning Distillation

Chengwei Dai, Kun Li, Wei Zhou +1

As Large Language Models (LLMs) scale up and gain powerful Chain-of-Thoughts (CoTs) reasoning abilities, practical resource constraints drive efforts to distill these capabilities…

cs.CL20231 cited

CT-GAT: Cross-Task Generative Adversarial Attack based on Transferability

Minxuan Lv, Chengwei Dai, Kun Li +2

Neural network models are vulnerable to adversarial examples, and adversarial transferability further increases the risk of adversarial attacks. Current methods based on transferab…

cs.CL2023

MeaeQ: Mount Model Extraction Attacks with Efficient Queries

Chengwei Dai, Minxuan Lv, Kun Li +1

We study model extraction attacks in natural language processing (NLP) where attackers aim to steal victim models by repeatedly querying the open Application Programming Interfaces…