Papers by Yujia Xie

7 papers
Recyclable Tuning for Continual Pre-training (2023.findings-acl)

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Challenge: Continual pre-training is the paradigm where pre-trained language models acquire fresh knowledge and gradually get upgraded.
Approach: They propose to use adapted weights to recycle old PLMs for continual pre-training . they propose to combine initialization and distillation methods to achieve better performance .
Outcome: The proposed method improves the convergence and performance of the upgraded PLM.
PodAgent: A Comprehensive Framework for Podcast Generation (2025.findings-acl)

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Challenge: Existing automatic audio generation methods struggle to generate podcast-like audio programs effectively.
Approach: They propose a framework for creating podcast-like audio programs that generates informative topic-discussion content by designing a multi-agent collaboration system, builds a voice pool and uses LLM-enhanced speech synthesis to generate expressive conversational speech.
Outcome: The proposed framework surpasses direct GPT-4 generation in topic-discussion dialogue content, and produces more expressive conversational speech.
MMAC: A Multilingual, Multimodal Alignment Framework for Cultural Grounding Evaluation (2026.acl-long)

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Challenge: Existing models lack cultural alignment across modalities and languages . a new framework to assess cultural awareness across linguistics and languages is needed .
Approach: They propose a framework that integrates tri-modally aligned cultural benchmarks and a five-dimensional evaluation protocol to assess cross-country awareness disparities.
Outcome: The proposed framework assesses cultural awareness disparities across modalities and languages . it is the first dataset aligned at the input level across text, image, and speech .
Exploring the Impact of Model Scaling on Parameter-Efficient Tuning (2023.emnlp-main)

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Challenge: Parameter-efficient tuning (PET) methods can drive large pre-trained language models by training only minimal parameters.
Approach: They propose a parameter-efficient tuning method that is compatible with a tunable module and uses a random number generator to optimize fewer table parameters.
Outcome: The proposed method is compatible with a tunable module and tested on 11 NLP tasks.
Personalized Abstractive Summarization by Tri-agent Generation Pipeline (2024.findings-eacl)

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Challenge: Existing research shows that large language models do not consistently satisfy users' preferences or expectations.
Approach: They propose a tri-agent generation pipeline that includes a generator, an instructor, and an editor to enhance output personalization.
Outcome: The proposed pipeline generates outputs that better meet user expectations on two abstractive summarization datasets.
WebCPM: Interactive Web Search for Chinese Long-form Question Answering (2023.acl-long)

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Challenge: Long-form question answering requires two procedures: information retrieval and information synthesis.
Approach: They propose a Chinese long-form question answering dataset called WebCPM . the dataset is based on a web search interface that engages with a search engine in real time .
Outcome: The proposed dataset generates answers that are no worse than human-written ones . the dataset is the first Chinese LFQA dataset .
Developing a Reliable, Fast, General-Purpose Hallucination Detection and Mitigation Service (2025.naacl-industry)

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Challenge: Hallucination is a problem in large language models that produce incorrect output . authors propose a reliable and high-speed production system to detect and rectify hallucinations .
Approach: They propose a high-speed production system that detects hallucinations in LLMs . they propose NER, natural language inference, span-based detection and a rewriting mechanism .
Outcome: The proposed system detects a wide range of hallucinations in LLM responses.

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