5 citations · 7 across the 7 of their papers we have counts for
6 papers · 1 filter
Beyond Cross-Lingual Transfer: Benchmarking Propagation Boundaries in Multilingual LLM Unlearning
Pengyang Shao, Chuanpeng Lu, Wei Qin +5
Large Language Model (LLM) unlearning aims to suppress target knowledge while preserving general capabilities. In multilingual settings, unlearning must additionally propagate with…
The Emergence of Abstract Thought in Large Language Models Beyond Any Language
Yuxin Chen, Yiran Zhao, Yang Zhang +7
As large language models (LLMs) continue to advance, their capacity to function effectively across a diverse range of languages has shown marked improvement. Preliminary studies ob…
Pruning General Large Language Models into Customized Expert Models
Yirao Zhao, Guizhen Chen, Kenji Kawaguchi +2
Large language models (LLMs) have revolutionized natural language processing, yet their substantial model sizes often require substantial computational resources. To preserve compu…
Unnatural Languages Are Not Bugs but Features for LLMs
Keyu Duan, Yiran Zhao, Zhili Feng +9
Large Language Models (LLMs) have been observed to process non-human-readable text sequences, such as jailbreak prompts, often viewed as a bug for aligned LLMs. In this work, we pr…
AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter Merging
Yiran Zhao, Wenxuan Zhang, Huiming Wang +2
As an effective alternative to the direct fine-tuning on target tasks in specific languages, cross-lingual transfer addresses the challenges of limited training data by decoupling…
How do Large Language Models Handle Multilingualism?
Yiran Zhao, Wenxuan Zhang, Guizhen Chen +2
Large language models (LLMs) have demonstrated impressive capabilities across diverse languages. This study explores how LLMs handle multilingualism. Based on observed language rat…