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cs.CL2025

DLP: Dynamic Layerwise Pruning in Large Language Models

Yuli Chen, Bo Cheng, Jiale Han +3

Pruning has recently been widely adopted to reduce the parameter scale and improve the inference efficiency of Large Language Models (LLMs). Mainstream pruning techniques often rel…

cs.CL2025

DialogueAgents: A Hybrid Agent-Based Speech Synthesis Framework for Multi-Party Dialogue

Xiang Li, Duyi Pan, Hongru Xiao +5

Speech synthesis is crucial for human-computer interaction, enabling natural and intuitive communication. However, existing datasets involve high construction costs due to manual a…

cs.CL20243 cited

Making Pre-trained Language Models Better Continual Few-Shot Relation Extractors

Shengkun Ma, Jiale Han, Yi Liang +1

Continual Few-shot Relation Extraction (CFRE) is a practical problem that requires the model to continuously learn novel relations while avoiding forgetting old ones with few label…

cs.CL2022

Generative Prompt Tuning for Relation Classification

Jiale Han, Shuai Zhao, Bo Cheng +2

Using prompts to explore the knowledge contained within pre-trained language models for downstream tasks has now become an active topic. Current prompt tuning methods mostly conver…

cs.CL2021

Exploring Task Difficulty for Few-Shot Relation Extraction

Jiale Han, Bo Cheng, Wei Lu

Few-shot relation extraction (FSRE) focuses on recognizing novel relations by learning with merely a handful of annotated instances. Meta-learning has been widely adopted for such…

cs.CL2021

Integrating Subgraph-aware Relation and DirectionReasoning for Question Answering

Xu Wang, Shuai Zhao, Bo Cheng +5

Question Answering (QA) models over Knowledge Bases (KBs) are capable of providing more precise answers by utilizing relation information among entities. Although effective, most o…