Search Results for author: Yung-Sung Chuang

Found 28 papers, 16 papers with code

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

2 code implementations7 Sep 2023 Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James Glass, Pengcheng He

Despite their impressive capabilities, large language models (LLMs) are prone to hallucinations, i. e., generating content that deviates from facts seen during pretraining.

Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images

1 code implementation CVPR 2023 Ming Y. Lu, Bowen Chen, Andrew Zhang, Drew F. K. Williamson, Richard J. Chen, Tong Ding, Long Phi Le, Yung-Sung Chuang, Faisal Mahmood

In this paper we present MI-Zero, a simple and intuitive framework for unleashing the zero-shot transfer capabilities of contrastively aligned image and text models on gigapixel histopathology whole slide images, enabling multiple downstream diagnostic tasks to be carried out by pretrained encoders without requiring any additional labels.

Multiple Instance Learning whole slide images

Revealing the Blind Spot of Sentence Encoder Evaluation by HEROS

no code implementations8 Jun 2023 Cheng-Han Chiang, Yung-Sung Chuang, James Glass, Hung-Yi Lee

We also show that even if two SEs have similar performance on STS benchmarks, they can have very different behavior on HEROS.


Expand, Rerank, and Retrieve: Query Reranking for Open-Domain Question Answering

1 code implementation26 May 2023 Yung-Sung Chuang, Wei Fang, Shang-Wen Li, Wen-tau Yih, James Glass

We propose EAR, a query Expansion And Reranking approach for improving passage retrieval, with the application to open-domain question answering.

Open-Domain Question Answering Passage Retrieval +1

SAIL: Search-Augmented Instruction Learning

no code implementations24 May 2023 Hongyin Luo, Yung-Sung Chuang, Yuan Gong, Tianhua Zhang, Yoon Kim, Xixin Wu, Danny Fox, Helen Meng, James Glass

Large language models (LLMs) have been significantly improved by instruction fine-tuning, but still lack transparency and the ability to utilize up-to-date knowledge and information.

Denoising Fact Checking +3

Interpretable Unified Language Checking

1 code implementation7 Apr 2023 Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, Wei Fang, Luc Gaitskell, Thomas Hartvigsen, Xixin Wu, Danny Fox, Helen Meng, James Glass

Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-task language checkers based on their latent representations of natural and social knowledge.

Fact Checking Fairness +2

C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval

1 code implementation7 Oct 2022 Andrew Rouditchenko, Yung-Sung Chuang, Nina Shvetsova, Samuel Thomas, Rogerio Feris, Brian Kingsbury, Leonid Karlinsky, David Harwath, Hilde Kuehne, James Glass

Inspired by the fact that English text-video retrieval outperforms other languages, we train a student model using input text in different languages to match the cross-modal predictions from teacher models using input text in English.

Knowledge Distillation Retrieval +2

Meta-learning for downstream aware and agnostic pretraining

no code implementations6 Jun 2021 Hongyin Luo, Shuyan Dong, Yung-Sung Chuang, Shang-Wen Li

Neural network pretraining is gaining attention due to its outstanding performance in natural language processing applications.


Investigating the Reordering Capability in CTC-based Non-Autoregressive End-to-End Speech Translation

1 code implementation Findings (ACL) 2021 Shun-Po Chuang, Yung-Sung Chuang, Chih-Chiang Chang, Hung-Yi Lee

We study the possibilities of building a non-autoregressive speech-to-text translation model using connectionist temporal classification (CTC), and use CTC-based automatic speech recognition as an auxiliary task to improve the performance.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Semi-Supervised Spoken Language Understanding via Self-Supervised Speech and Language Model Pretraining

1 code implementation26 Oct 2020 Cheng-I Lai, Yung-Sung Chuang, Hung-Yi Lee, Shang-Wen Li, James Glass

Much recent work on Spoken Language Understanding (SLU) is limited in at least one of three ways: models were trained on oracle text input and neglected ASR errors, models were trained to predict only intents without the slot values, or models were trained on a large amount of in-house data.

Language Modelling Spoken Language Understanding

What makes multilingual BERT multilingual?

no code implementations20 Oct 2020 Chi-Liang Liu, Tsung-Yuan Hsu, Yung-Sung Chuang, Hung-Yi Lee

Recently, multilingual BERT works remarkably well on cross-lingual transfer tasks, superior to static non-contextualized word embeddings.

Cross-Lingual Transfer Word Embeddings

Dual Inference for Improving Language Understanding and Generation

1 code implementation Findings of the Association for Computational Linguistics 2020 Shang-Yu Su, Yung-Sung Chuang, Yun-Nung Chen

Natural language understanding (NLU) and Natural language generation (NLG) tasks hold a strong dual relationship, where NLU aims at predicting semantic labels based on natural language utterances and NLG does the opposite.

Natural Language Understanding Text Generation

Lifelong Language Knowledge Distillation

1 code implementation EMNLP 2020 Yung-Sung Chuang, Shang-Yu Su, Yun-Nung Chen

It is challenging to perform lifelong language learning (LLL) on a stream of different tasks without any performance degradation comparing to the multi-task counterparts.

Knowledge Distillation Language Modelling +3

A Study of Cross-Lingual Ability and Language-specific Information in Multilingual BERT

no code implementations20 Apr 2020 Chi-Liang Liu, Tsung-Yuan Hsu, Yung-Sung Chuang, Hung-Yi Lee

Recently, multilingual BERT works remarkably well on cross-lingual transfer tasks, superior to static non-contextualized word embeddings.

Cross-Lingual Transfer Translation +1

SpeechBERT: An Audio-and-text Jointly Learned Language Model for End-to-end Spoken Question Answering

no code implementations25 Oct 2019 Yung-Sung Chuang, Chi-Liang Liu, Hung-Yi Lee, Lin-shan Lee

In addition to the potential of end-to-end SQA, the SpeechBERT can also be considered for many other spoken language understanding tasks just as BERT for many text processing tasks.

Language Modelling Question Answering +2

Robust Chinese Word Segmentation with Contextualized Word Representations

no code implementations17 Jan 2019 Yung-Sung Chuang

In recent years, after the neural-network-based method was proposed, the accuracy of the Chinese word segmentation task has made great progress.

Chinese Word Segmentation Language Modelling

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