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20242026
most citedMitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal

3 citations · 4 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2026

Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection

Hui Li, Zhongquan Jian, Jinsong Su +1

Automatic misinformation detection performs well when deception is visible in what an article explicitly states. However, some misinformation articles remain locally coherent and o…

cs.CV2026

RASR: Retrieval-Augmented Semantic Reasoning for Fake News Video Detection

Hui Li, Peien Ding, Jun Li +5

Multimodal fake news video detection is a crucial research direction for maintaining the credibility of online information. Existing studies primarily verify content authenticity b…

cs.CL2025

Locate-and-Focus: Enhancing Terminology Translation in Speech Language Models

Suhang Wu, Jialong Tang, Chengyi Yang +6

Direct speech translation (ST) has garnered increasing attention nowadays, yet the accurate translation of terminology within utterances remains a great challenge. In this regard,…

cs.CL2024

Not All Languages are Equal: Insights into Multilingual Retrieval-Augmented Generation

Suhang Wu, Jialong Tang, Baosong Yang +5

RALMs (Retrieval-Augmented Language Models) broaden their knowledge scope by incorporating external textual resources. However, the multilingual nature of global knowledge necessit…

cs.CL2024

A Learning Rate Path Switching Training Paradigm for Version Updates of Large Language Models

Zhihao Wang, Shiyu Liu, Jianheng Huang +5

Due to the continuous emergence of new data, version updates have become an indispensable requirement for Large Language Models (LLMs). The training paradigms for version updates o…

cs.CL2024

Mitigating the Negative Impact of Over-association for Conversational Query Production

Ante Wang, Linfeng Song, Zijun Min +4

Conversational query generation aims at producing search queries from dialogue histories, which are then used to retrieve relevant knowledge from a search engine to help knowledge-…

cs.CL2024

Towards Better Graph-based Cross-document Relation Extraction via Non-bridge Entity Enhancement and Prediction Debiasing

Hao Yue, Shaopeng Lai, Chengyi Yang +3

Cross-document Relation Extraction aims to predict the relation between target entities located in different documents. In this regard, the dominant models commonly retain useful i…

cs.CL2024★ 1 cited

On the Information Redundancy in Non-Autoregressive Translation

Zhihao Wang, Longyue Wang, Jinsong Su +2

Token repetition is a typical form of multi-modal problem in fully non-autoregressive translation (NAT). In this work, we revisit the multi-modal problem in recently proposed NAT m…

cs.CL2024★ 3 cited

Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal

Jianheng Huang, Leyang Cui, Ante Wang +5

Large language models (LLMs) suffer from catastrophic forgetting during continual learning. Conventional rehearsal-based methods rely on previous training data to retain the model'…