Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Fine-Tuning Large Language Models to Translate: Will a Touch of Noisy Data in Misaligned Languages Suffice?

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Dawei Zhu

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Assessing "Implicit" Retrieval Robustness of Large Language Models.

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[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

To Preserve or To Compress: An In-Depth Study of Connector Selection in Multimodal Large Language Models.

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Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

LawBench: Benchmarking Legal Knowledge of Large Language Models.

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Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

The Accuracy Paradox in RLHF: When Better Reward Models Don't Yield Better Language Models.

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Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects.

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[DOI]

David Ifeoluwa Adelani

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis.

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Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Software Engineering Tasks.

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CoRR, 2023

LawBench: Benchmarking Legal Knowledge of Large Language Models.

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[DOI]

CoRR, 2023

Weaker Than You Think: A Critical Look atWeakly Supervised Learning.

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[DOI]

CoRR, 2023

xPQA: Cross-Lingual Product Question Answering across 12 Languages.

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[DOI]

CoRR, 2023

Meta Self-Refinement for Robust Learning with Weak Supervision.

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[DOI]

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Neural Ranking with Weak Supervision for Open-Domain Question Answering : A Survey.

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[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Weaker Than You Think: A Critical Look at Weakly Supervised Learning.

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[DOI]

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

xPQA: Cross-Lingual Product Question Answering in 12 Languages.

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Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023

2022

MDIA: A Benchmark for Multilingual Dialogue Generation in 46 Languages.

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[DOI]

CoRR, 2022

Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Survey.

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[DOI]

CoRR, 2022

A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation.

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[DOI]

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

AST-Trans: Code Summarization with Efficient Tree-Structured Attention.

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[DOI]

Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

FocusQA: Open-Domain Question Answering with a Context in Focus.

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[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

RoCBert: Robust Chinese Bert with Multimodal Contrastive Pretraining.

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Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

From Rewriting to Remembering: Common Ground for Conversational QA Models.

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Proceedings of the 4th Workshop on NLP for Conversational AI, 2022

2021

Deep latent-variable models for neural text generation.

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[DOI]

Xiaoyu Shen

PhD thesis, 2021

Learning Fine-Grained Fact-Article Correspondence in Legal Cases.

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[DOI]

IEEE ACM Trans. Audio Speech Lang. Process., 2021

Knowledge-enhanced Session-based Recommendation with Temporal Transformer.

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[DOI]

CoRR, 2021

Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer.

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[DOI]

CoRR, 2021

Learning Fine-grained Fact-Article Correspondence in Legal Cases.

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[DOI]

CoRR, 2021

AST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization.

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[DOI]

Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

The SelectGen Challenge: Finding the Best Training Samples for Few-Shot Neural Text Generation.

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Proceedings of the 14th International Conference on Natural Language Generation, 2021

Preventing Author Profiling through Zero-Shot Multilingual Back-Translation.

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[DOI]

David Ifeoluwa Adelani

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Neural Data-to-Text Generation with LM-based Text Augmentation.

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[DOI]

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Question Rewriting for Open-Domain Conversational QA: Best Practices and Limitations.

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Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

On Training Instance Selection for Few-Shot Neural Text Generation.

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Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Integrating Image Captioning with Rule-based Entity Masking.

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[DOI]

Aditya Mogadala

Xiaoyu Shen

Dietrich Klakow

CoRR, 2020

Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence.

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[DOI]

CoRR, 2020

Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training.

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[DOI]

Ernie Chang

David Ifeoluwa Adelani

Xiaoyu Shen

Vera Demberg

Proceedings of the 1st AfricaNLP Workshop Proceedings, 2020

MovieChats: Chat like Humans in a Closed Domain.

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Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool.

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Proceedings of the 28th International Conference on Computational Linguistics, 2020

Diversifying Dialogue Generation with Non-Conversational Text.

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[DOI]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence.

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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Improving Latent Alignment in Text Summarization by Generalizing the Pointer Generator.

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Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Select and Attend: Towards Controllable Content Selection in Text Generation.

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Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Unsupervised Rewriter for Multi-Sentence Compression.

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Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Improving Multi-turn Dialogue Modelling with Utterance ReWriter.

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[DOI]

Hui Su