---
title: "Graham Neubig — papers"
description: "Graham Neubig: 44 papers in the Elamur Research library (2011–2025) — our summary of each, its ideas, references and who cites it."
canonical: "https://research.elamur.ai/free/en/authors/graham-neubig/"
---
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# Graham Neubig

44 papers on this site (2011–2025)

[OpenAlex](https://openalex.org/A5068811427) · [ORCID](https://orcid.org/0000-0002-2072-3789) · h-index 72 · 630 works · 24683 citations (openalex-snapshot, 2026-10-14)

Profile data from OpenAlex; authors with the same name are not always told apart.

- [Demystifying Long Chain-of-Thought Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/) — Edward Yeo, Yuxuan Tong, Morry Niu, et al. · 2025
- [Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models](https://md.research.elamur.ai/free/en/papers/kim-2024-prometheus-2-open-source-language/) — Seungone Kim, Juyoung Suk, Shayne Longpre, et al. · 2024
- [VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/) — Jing Yu Koh, Robert Lo, Lawrence Jang, et al. · 2024
- [Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) — Patrick Fernandes, Aman Madaan, Emmy Liu, et al. · 2023
- [ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages](https://md.research.elamur.ai/free/en/papers/robinson-2023-chatgpt-mt-competitive-high-but/) — Nathaniel Robinson, Perez Ogayo, David R. Mortensen, et al. · 2023
- [Crossing the Threshold: Idiomatic Machine Translation through Retrieval Augmentation and Loss Weighting](https://md.research.elamur.ai/free/en/papers/liu-2023-crossing-threshold-idiomatic-machine-translation/) — Emmy Liu, Aditi Chaudhary, Graham Neubig · 2023
- [FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios](https://md.research.elamur.ai/free/en/papers/chern-2023-factool-factuality-detection-generative-ai/) — I-Chun Chern, Steffi Chern, Shiqi Chen, et al. · 2023
- [SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents](https://md.research.elamur.ai/free/en/papers/zhou-2023-sotopia-interactive-evaluation-social-intelligence/) — Xuhui Zhou, Hao Zhu, Leena Mathur, et al. · 2023
- [The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-devil-is-errors-leveraging-large/) — Patrick Fernandes, Daniel Deutsch, Mara Finkelstein, et al. · 2023
- [WebArena: A Realistic Web Environment for Building Autonomous Agents](https://md.research.elamur.ai/free/en/papers/zhou-2023-webarena-realistic-web-environment-building/) — Shuyan Zhou, Frank F. Xu, Hao Zhu, et al. · 2023
- [BRIO: Bringing Order to Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/liu-2022-brio-bringing-order-abstractive-summarization/) — Yixin Liu, Pengfei Liu, Dragomir Radev, et al. · 2022
- [MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/adelani-2022-masakhaner-2-0-africa-centric/) — David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder, et al. · 2022
- [Quality-Aware Decoding for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/fernandes-2022-quality-aware-decoding-neural-machine/) — Patrick Fernandes, António Farinhas, Ricardo Rei, et al. · 2022
- [Systematic Inequalities in Language Technology Performance across the World's Languages](https://md.research.elamur.ai/free/en/papers/blasi-2022-systematic-inequalities-language-technology-performance/) — Damian Blasi, Antonios Anastasopoulos, Graham Neubig · 2022
- [BARTScore: Evaluating Generated Text as Text Generation](https://md.research.elamur.ai/free/en/papers/yuan-2021-bartscore-evaluating-generated-text-text/) — Weizhe Yuan, Graham Neubig, Pengfei Liu · 2021
- [Detecting Hallucinated Content in Conditional Neural Sequence Generation](https://md.research.elamur.ai/free/en/papers/zhou-2021-detecting-hallucinated-content-conditional-neural/) — Chunting Zhou, Graham Neubig, Jiatao Gu, et al. · 2021
- [GSum: A General Framework for Guided Neural Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/dou-2021-gsum-general-framework-guided-neural/) — Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, et al. · 2021
- [MasakhaNER: Named Entity Recognition for African Languages](https://md.research.elamur.ai/free/en/papers/adelani-2021-masakhaner-named-entity-recognition-african/) — David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, et al. · 2021
- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/) — Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al. · 2021
- [Towards a Unified View of Parameter-Efficient Transfer Learning](https://md.research.elamur.ai/free/en/papers/he-2021-towards-unified-view-parameter-efficient/) — Junxian He, Chunting Zhou, Xuezhe Ma, et al. · 2021
- [XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/ruder-2021-xtreme-r-more-challenging-nuanced/) — Sebastian Ruder, Noah Constant, Jan Botha, et al. · 2021
- [How Can We Know What Language Models Know?](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/) — Zhengbao Jiang, Frank F. Xu, Jun Araki, et al. · 2020
- [Politeness Transfer: A Tag and Generate Approach](https://md.research.elamur.ai/free/en/papers/madaan-2020-politeness-transfer-tag-generate-approach/) — Aman Madaan, Amrith Setlur, Tanmay Parekh, et al. · 2020
- [Re-evaluating Evaluation in Text Summarization](https://md.research.elamur.ai/free/en/papers/bhandari-2020-re-evaluating-evaluation-text-summarization/) — Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, et al. · 2020
- [TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/) — Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al. · 2020
- [Weight Poisoning Attacks on Pretrained Models](https://md.research.elamur.ai/free/en/papers/kurita-2020-weight-poisoning-attacks-pretrained-models/) — Keita Kurita, Paul Michel, Graham Neubig · 2020
- [XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization](https://md.research.elamur.ai/free/en/papers/hu-2020-xtreme-massively-multilingual-multi-task/) — Junjie Hu, Sebastian Ruder, Aditya Siddhant, et al. · 2020
- [Are Sixteen Heads Really Better than One?](https://md.research.elamur.ai/free/en/papers/michel-2019-sixteen-heads-really-better-than/) — Paul Michel, Omer Levy, Graham Neubig · 2019
- [Beyond BLEU: Training Neural Machine Translation with Semantic Similarity](https://md.research.elamur.ai/free/en/papers/wieting-2019-beyond-bleu-training-neural-machine/) — John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, et al. · 2019
- [compare-mt: A Tool for Holistic Comparison of Language Generation Systems](https://md.research.elamur.ai/free/en/papers/neubig-2019-compare-mt-tool-holistic-comparison/) — Graham Neubig, Zi-Yi Dou, Junjie Hu, et al. · 2019
- [Handling Syntactic Divergence in Low-resource Machine Translation](https://md.research.elamur.ai/free/en/papers/zhou-2019-handling-syntactic-divergence-low-resource/) — Chunting Zhou, Xuezhe Ma, Junjie Hu, et al. · 2019
- [Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow](https://md.research.elamur.ai/free/en/papers/yin-2018-learning-mine-aligned-code-natural/) — Pengcheng Yin, Bowen Deng, Edgar Chen, et al. · 2018
- [MTNT: A Testbed for Machine Translation of Noisy Text](https://md.research.elamur.ai/free/en/papers/michel-2018-mtnt-testbed-machine-translation-noisy/) — Paul Michel, Graham Neubig · 2018
- [Neural Cross-Lingual Named Entity Recognition with Minimal Resources](https://md.research.elamur.ai/free/en/papers/xie-2018-neural-cross-lingual-named-entity/) — Jiateng Xie, Zhilin Yang, Graham Neubig, et al. · 2018
- [Rapid Adaptation of Neural Machine Translation to New Languages](https://md.research.elamur.ai/free/en/papers/neubig-2018-rapid-adaptation-neural-machine-translation/) — Graham Neubig, Junjie Hu · 2018
- [SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2018-switchout-efficient-data-augmentation-algorithm/) — Xinyi Wang, Hieu Pham, Zihang Dai, et al. · 2018
- [When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?](https://md.research.elamur.ai/free/en/papers/qi-2018-when-why-are-pre-trained/) — Ye Qi, Devendra Sachan, Matthieu Felix, et al. · 2018
- [A Syntactic Neural Model for General-Purpose Code Generation](https://md.research.elamur.ai/free/en/papers/yin-2017-syntactic-neural-model-general-purpose/) — Pengcheng Yin, Graham Neubig · 2017
- [DyNet: The Dynamic Neural Network Toolkit](https://md.research.elamur.ai/free/en/papers/neubig-2017-dynet-dynamic-neural-network-toolkit/) — Graham Neubig, Chris Dyer, Yoav Goldberg, et al. · 2017
- [Learning to Translate in Real-time with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gu-2017-learning-translate-real-time-neural/) — Jiatao Gu, Graham Neubig, Kyunghyun Cho, et al. · 2017
- [Stronger Baselines for Trustable Results in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/denkowski-2017-stronger-baselines-trustable-results-neural/) — Michael Denkowski, Graham Neubig · 2017
- [Controlling Output Length in Neural Encoder-Decoders](https://md.research.elamur.ai/free/en/papers/kikuchi-2016-controlling-output-length-neural-encoder/) — Yuta Kikuchi, Graham Neubig, Ryohei Sasano, et al. · 2016
- [Incorporating Discrete Translation Lexicons into Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/arthur-2016-incorporating-discrete-translation-lexicons-into/) — Philip Arthur, Graham Neubig, Satoshi Nakamura · 2016
- [Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis](https://md.research.elamur.ai/free/en/papers/neubig-2011-pointwise-prediction-robust-adaptable-japanese/) — Graham Neubig, Yosuke Nakata, Shinsuke Mori · 2011