Effective Dimensionality Reduction for Word Embeddings. - Vikas Raunak (CoRR, 2017)

Learned in Speech Recognition: Contextual Acoustic Word Embeddings. - Shruti Palaskar; Vikas Raunak; Florian Metze (ICASSP, 2019)

On Leveraging the Visual Modality for Neural Machine Translation. - Vikas Raunak; Sang Keun Choe; Quanyang Lu; Yi Xu; Florian Metze (INLG, 2019)

Effective Dimensionality Reduction for Word Embeddings. - Vikas Raunak; Vivek Gupta 001; Florian Metze (RepL4NLP@ACL, 2019)

On Compositionality in Neural Machine Translation. - Vikas Raunak; Vaibhav Kumar; Florian Metze (CoRR, 2019)

Ranking Clarification Questions via Natural Language Inference. - Vaibhav Kumar; Vikas Raunak; Jamie Callan (CIKM, 2020)

On Long-Tailed Phenomena in Neural Machine Translation. - Vikas Raunak; Siddharth Dalmia; Vivek Gupta 001; Florian Metze (EMNLP (Findings), 2020)

On Dimensional Linguistic Properties of the Word Embedding Space. - Vikas Raunak; Vaibhav Kumar; Vivek Gupta 001; Florian Metze (RepL4NLP@ACL, 2020)

Searchable Hidden Intermediates for End-to-End Models of Decomposable Sequence Tasks. - Siddharth Dalmia; Brian Yan; Vikas Raunak; Florian Metze; Shinji Watanabe 001 (NAACL-HLT, 2021)

The Curious Case of Hallucinations in Neural Machine Translation. - Vikas Raunak; Arul Menezes; Marcin Junczys-Dowmunt (NAACL-HLT, 2021)

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics. - Sebastian Gehrmann; Tosin P. Adewumi; Karmanya Aggarwal; Pawan Sasanka Ammanamanchi; Aremu Anuoluwapo; Antoine Bosselut; Khyathi Raghavi Chandu; Miruna-Adriana Clinciu; Dipanjan Das 001; Kaustubh D. Dhole; Wanyu Du; Esin Durmus; et al. (CoRR, 2021)

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation. - Kaustubh D. Dhole; Varun Gangal; Sebastian Gehrmann; Aadesh Gupta; Zhenhao Li; Saad Mahamood; Abinaya Mahendiran; Simon Mille; Ashish Srivastava; Samson Tan; Tongshuang Wu; Jascha Sohl-Dickstein; et al. (CoRR, 2021)

Finding Memo: Extractive Memorization in Constrained Sequence Generation Tasks. - Vikas Raunak; Arul Menezes (EMNLP (Findings), 2022)

SALTED: A Framework for SAlient Long-tail Translation Error Detection. - Vikas Raunak; Matt Post; Arul Menezes (EMNLP (Findings), 2022)

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code. - Sebastian Gehrmann; Abhik Bhattacharjee; Abinaya Mahendiran; Alex Wang; Alexandros Papangelis; Aman Madaan; Angelina McMillan-Major; Anna Shvets; Ashish Upadhyay; Bingsheng Yao; Bryan Wilie; Chandra Bhagavatula; et al. (CoRR, 2022)

Rank-One Editing of Encoder-Decoder Models. - Vikas Raunak; Arul Menezes (CoRR, 2022)

Operationalizing Specifications, In Addition to Test Sets for Evaluating Constrained Generative Models. - Vikas Raunak; Matt Post; Arul Menezes (CoRR, 2022)

Do GPTs Produce Less Literal Translations? - Vikas Raunak; Arul Menezes; Matt Post; Hany Hassan (ACL (2), 2023)

Dissecting In-Context Learning of Translations in GPT-3. - Vikas Raunak; Arul Menezes; Hany Hassan Awadalla (EMNLP (Findings), 2023)

Leveraging GPT-4 for Automatic Translation Post-Editing. - Vikas Raunak; Amr Sharaf; Yiren Wang; Hany Hassan Awadalla; Arul Menezes (EMNLP (Findings), 2023)

Evaluating Metrics for Document-context Evaluation in Machine Translation. - Vikas Raunak; Tom Kocmi; Matt Post (WMT, 2023)

How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation. - Amr Hendy; Mohamed Abdelrehim; Amr Sharaf; Vikas Raunak; Mohamed Gabr; Hitokazu Matsushita; Young Jin Kim 001; Mohamed Afify; Hany Hassan Awadalla (CoRR, 2023)

Leveraging GPT-4 for Automatic Translation Post-Editing. - Vikas Raunak; Amr Sharaf; Hany Hassan Awadallah; Arul Menezes (CoRR, 2023)

Dissecting In-Context Learning of Translations in GPTs. - Vikas Raunak; Hany Hassan Awadalla; Arul Menezes (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

SLIDE: Reference-free Evaluation for Machine Translation using a Sliding Document Window. - Vikas Raunak; Tom Kocmi; Matt Post (NAACL (Short Papers), 2024)

On Instruction-Finetuning Neural Machine Translation Models. - Vikas Raunak; Roman Grundkiewicz; Marcin Junczys-Dowmunt (WMT, 2024)

Memorization Inheritance in Sequence-Level Knowledge Distillation for Neural Machine Translation. - Verna Dankers; Vikas Raunak (CoRR, 2025)