37 citations · 85 across the 24 of their papers we have counts for
25 papers
Logbook: Extremely Long-form Audio Event Understanding
Kwanghee Choi, Suwon Shon, Dmitriy Serdyuk +7
Audio benchmarks are built around short, pre-segmented clips, limiting model design to brief inputs or fixed vocabularies. To close this gap, we introduce Logbook, a benchmark for…
FactAlign: Long-form Factuality Alignment of Large Language Models
Chao-Wei Huang, Yun-Nung Chen
Large language models have demonstrated significant potential as the next-generation information access engines. However, their reliability is hindered by issues of hallucination a…
PairDistill: Pairwise Relevance Distillation for Dense Retrieval
Chao-Wei Huang, Yun-Nung Chen
Effective information retrieval (IR) from vast datasets relies on advanced techniques to extract relevant information in response to queries. Recent advancements in dense retrieval…
LLMs are Biased Evaluators But Not Biased for Retrieval Augmented Generation
Yen-Shan Chen, Jing Jin, Peng-Ting Kuo +2
Recent studies have demonstrated that large language models (LLMs) exhibit significant biases in evaluation tasks, particularly in preferentially rating and favoring self-generated…
A Survey of Generative Information Retrieval
Tzu-Lin Kuo, Tzu-Wei Chiu, Tzung-Sheng Lin +3
Generative Retrieval (GR) is an emerging paradigm in information retrieval that leverages generative models to directly map queries to relevant document identifiers (DocIDs) withou…
Editing the Mind of Giants: An In-Depth Exploration of Pitfalls of Knowledge Editing in Large Language Models
Cheng-Hsun Hsueh, Paul Kuo-Ming Huang, Tzu-Han Lin +4
Knowledge editing is a rising technique for efficiently updating factual knowledge in large language models (LLMs) with minimal alteration of parameters. However, recent studies ha…
Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization
Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao +4
The concept of persona, originally adopted in dialogue literature, has re-surged as a promising framework for tailoring large language models (LLMs) to specific context (e.g., pers…
InstUPR : Instruction-based Unsupervised Passage Reranking with Large Language Models
Chao-Wei Huang, Yun-Nung Chen
This paper introduces InstUPR, an unsupervised passage reranking method based on large language models (LLMs). Different from existing approaches that rely on extensive training wi…
Unsupervised Multilingual Dense Retrieval via Generative Pseudo Labeling
Chao-Wei Huang, Chen-An Li, Tsu-Yuan Hsu +2
Dense retrieval methods have demonstrated promising performance in multilingual information retrieval, where queries and documents can be in different languages. However, dense ret…
CONVERSER: Few-Shot Conversational Dense Retrieval with Synthetic Data Generation
Chao-Wei Huang, Chen-Yu Hsu, Tsu-Yuan Hsu +2
Conversational search provides a natural interface for information retrieval (IR). Recent approaches have demonstrated promising results in applying dense retrieval to conversation…
Open-Domain Conversational Question Answering with Historical Answers
Hung-Chieh Fang, Kuo-Han Hung, Chao-Wei Huang +1
Open-domain conversational question answering can be viewed as two tasks: passage retrieval and conversational question answering, where the former relies on selecting candidate pa…
Controllable User Dialogue Act Augmentation for Dialogue State Tracking
Chun-Mao Lai, Ming-Hao Hsu, Chao-Wei Huang +1
Prior work has demonstrated that data augmentation is useful for improving dialogue state tracking. However, there are many types of user utterances, while the prior method only co…
PLM-ICD: Automatic ICD Coding with Pretrained Language Models
Chao-Wei Huang, Shang-Chi Tsai, Yun-Nung Chen
Automatically classifying electronic health records (EHRs) into diagnostic codes has been challenging to the NLP community. State-of-the-art methods treated this problem as a multi…
Miutsu: NTU's TaskBot for the Alexa Prize
Yen-Ting Lin, Hui-Chi Kuo, Ze-Song Xu +5
This paper introduces Miutsu, National Taiwan University's Alexa Prize TaskBot, which is designed to assist users in completing tasks requiring multiple steps and decisions in two…
Islander: A Real-Time News Monitoring and Analysis System
Chao-Wei Huang, Kai-Chou Yang, Zi-Yuan Chen +8
With thousands of news articles from hundreds of sources distributed and shared every day, news consumption and information acquisition have been increasingly difficult for readers…
Federated Natural Language Generation for Personalized Dialogue System
Yujie Lu, Chao Huang, Huanli Zhan +1
Neural conversational models have long suffered from the problem of inconsistency and lacking coherent personality. To address the issue, persona-based models capturing individual…
Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access Track in DSTC9
Seokhwan Kim, Mihail Eric, Behnam Hedayatnia +4
Most prior work on task-oriented dialogue systems are restricted to a limited coverage of domain APIs, while users oftentimes have domain related requests that are not covered by t…
Overview of the Ninth Dialog System Technology Challenge: DSTC9
Chulaka Gunasekara, Seokhwan Kim, Luis Fernando D'Haro +36
This paper introduces the Ninth Dialog System Technology Challenge (DSTC-9). This edition of the DSTC focuses on applying end-to-end dialog technologies for four distinct tasks in…
Adapting Pretrained Transformer to Lattices for Spoken Language Understanding
Chao-Wei Huang, Yun-Nung Chen
Lattices are compact representations that encode multiple hypotheses, such as speech recognition results or different word segmentations. It is shown that encoding lattices as oppo…
Learning Spoken Language Representations with Neural Lattice Language Modeling
Chao-Wei Huang, Yun-Nung Chen
Pre-trained language models have achieved huge improvement on many NLP tasks. However, these methods are usually designed for written text, so they do not consider the properties o…
Towards Unsupervised Language Understanding and Generation by Joint Dual Learning
Shang-Yu Su, Chao-Wei Huang, Yun-Nung Chen
In modular dialogue systems, natural language understanding (NLU) and natural language generation (NLG) are two critical components, where NLU extracts the semantics from the given…
Learning ASR-Robust Contextualized Embeddings for Spoken Language Understanding
Chao-Wei Huang, Yun-Nung Chen
Employing pre-trained language models (LM) to extract contextualized word representations has achieved state-of-the-art performance on various NLP tasks. However, applying this tec…
Dual Supervised Learning for Natural Language Understanding and Generation
Shang-Yu Su, Chao-Wei Huang, Yun-Nung Chen
Natural language understanding (NLU) and natural language generation (NLG) are both critical research topics in the NLP field. Natural language understanding is to extract the core…
Learning Multi-Level Information for Dialogue Response Selection by Highway Recurrent Transformer
Ting-Rui Chiang, Chao-Wei Huang, Shang-Yu Su +1
With the increasing research interest in dialogue response generation, there is an emerging branch formulating this task as selecting next sentences, where given the partial dialog…