Earth Mover's Distance Pooling over Siamese LSTMs for Automatic Short Answer Grading. - Sachin Kumar 009; Soumen Chakrabarti; Shourya Roy (IJCAI, 2017)

Mining & Summarizing E-petitions for Enhanced Understanding of Public Opinion. - Shreshtha Mundra; Sachin Kumar 009; Manjira Sinha; Sandya Mannarswamy (CIKM, 2018)

A Margin-based Loss with Synthetic Negative Samples for Continuous-output Machine Translation. - Gayatri Bhat; Sachin Kumar 009; Yulia Tsvetkov (NGT@EMNLP-IJCNLP, 2019)

Topics to Avoid: Demoting Latent Confounds in Text Classification. - Sachin Kumar 009; Shuly Wintner; Noah A. Smith; Yulia Tsvetkov (EMNLP/IJCNLP (1), 2019)

Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs. - Sachin Kumar 009; Yulia Tsvetkov (ICLR (Poster), 2019)

A Deep Reinforced Model for Zero-Shot Cross-Lingual Summarization with Bilingual Semantic Similarity Rewards. - Zi-Yi Dou; Sachin Kumar 009; Yulia Tsvetkov (NGT@ACL, 2020)

End-to-End Differentiable GANs for Text Generation. - Sachin Kumar 009; Yulia Tsvetkov (ICBINB@NeurIPS, 2020)

Neural Abstractive Summarization with Structural Attention. - Tanya Chowdhury; Sachin Kumar 009; Tanmoy Chakraborty 002 (IJCAI, 2020)

Machine Translation into Low-resource Language Varieties. - Sachin Kumar 009; Antonios Anastasopoulos; Shuly Wintner; Yulia Tsvetkov (ACL/IJCNLP (2), 2021)

Controlled Text Generation as Continuous Optimization with Multiple Constraints. - Sachin Kumar 009; Eric Malmi; Aliaksei Severyn; Yulia Tsvetkov (NeurIPS, 2021)

An Exploration of Data Augmentation Techniques for Improving English to Tigrinya Translation. - Lidia Kidane; Sachin Kumar 009; Yulia Tsvetkov (AfricaNLP, 2021)

Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs. - Monisha Jegadeesan; Sachin Kumar 009; John Wieting; Yulia Tsvetkov (CoRR, 2021)

Gradient-based Constrained Sampling from Language Models. - Sachin Kumar 009; Biswajit Paria; Yulia Tsvetkov (EMNLP, 2022)

Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation. - Melanie Sclar; Peter West; Sachin Kumar 009; Yulia Tsvetkov; Yejin Choi 001 (EMNLP, 2022)

Accepted Tutorials at The Web Conference 2022. - Riccardo Tommasini 001; Senjuti Basu Roy; Xuan Wang 008; Hongwei Wang; Heng Ji 001; Jiawei Han 001; Preslav Nakov; Giovanni Da San Martino; Firoj Alam; Markus Schedl; Elisabeth Lex; Akash Bharadwaj; et al. (WWW (Companion Volume), 2022)

Constrained Sampling from Language Models via Langevin Dynamics in Embedding Spaces. - Sachin Kumar 009; Biswajit Paria; Yulia Tsvetkov (CoRR, 2022)

SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control. - Xiaochuang Han; Sachin Kumar 009; Yulia Tsvetkov (ACL (1), 2023)

On the Blind Spots of Model-Based Evaluation Metrics for Text Generation. - Tianxing He; Jingyu Zhang; Tianle Wang 003; Sachin Kumar 009; Kyunghyun Cho; James R. Glass; Yulia Tsvetkov (ACL (1), 2023)

Minding Language Models' (Lack of) Theory of Mind: A Plug-and-Play Multi-Character Belief Tracker. - Melanie Sclar; Sachin Kumar 009; Peter West; Alane Suhr; Yejin Choi 001; Yulia Tsvetkov (ACL (1), 2023)

Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey. - Sachin Kumar 009; Vidhisha Balachandran; Lucille Njoo; Antonios Anastasopoulos; Yulia Tsvetkov (EACL, 2023)

Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models. - Orevaoghene Ahia; Sachin Kumar 009; Hila Gonen; Jungo Kasai; David R. Mortensen; Noah A. Smith; Yulia Tsvetkov (EMNLP, 2023)

Assessing Language Model Deployment with Risk Cards. - Leon Derczynski; Hannah Rose Kirk; Vidhisha Balachandran; Sachin Kumar 009; Yulia Tsvetkov; Mark R. Leiser; Saif Mohammad (CoRR, 2023)

SSD-2: Scaling and Inference-time Fusion of Diffusion Language Models. - Xiaochuang Han; Sachin Kumar 009; Yulia Tsvetkov; Marjan Ghazvininejad (CoRR, 2023)

What Constitutes a Faithful Summary? Preserving Author Perspectives in News Summarization. - Yuhan Liu; Shangbin Feng; Xiaochuang Han; Vidhisha Balachandran; Chan Young Park; Sachin Kumar 009; Yulia Tsvetkov (CoRR, 2023)

Optimization Methods for Improving Diversity in Language Technologies - Sachin Kumar 009 (2023)

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. - Luca Soldaini; Rodney Kinney; Akshita Bhagia; Dustin Schwenk; David Atkinson; Russell Authur; Ben Bogin; Khyathi Raghavi Chandu; Jennifer Dumas; Yanai Elazar; Valentin Hofmann; Ananya Harsh Jha; et al. (ACL (1), 2024)

Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions. - Sachin Kumar 009; Chan Young Park; Yulia Tsvetkov (ICLR, 2024)

David helps Goliath: Inference-Time Collaboration Between Small Specialized and Large General Diffusion LMs. - Xiaochuang Han; Sachin Kumar 009; Yulia Tsvetkov; Marjan Ghazvininejad (NAACL-HLT, 2024)

P³Sum: Preserving Author's Perspective in News Summarization with Diffusion Language Models. - Yuhan Liu; Shangbin Feng; Xiaochuang Han; Vidhisha Balachandran; Chan Young Park; Sachin Kumar 009; Yulia Tsvetkov (NAACL-HLT, 2024)

MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization. - Orevaoghene Ahia; Sachin Kumar 009; Hila Gonen; Valentin Hofmann; Tomasz Limisiewicz; Yulia Tsvetkov; Noah A. Smith (NeurIPS, 2024)

The Art of Saying No: Contextual Noncompliance in Language Models. - Faeze Brahman; Sachin Kumar 009; Vidhisha Balachandran; Pradeep Dasigi; Valentina Pyatkin; Abhilasha Ravichander; Sarah Wiegreffe; Nouha Dziri; Khyathi Raghavi Chandu; Jack Hessel; Yulia Tsvetkov; Noah A. Smith; et al. (NeurIPS, 2024)

WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models. - Liwei Jiang; Kavel Rao; Seungju Han 002; Allyson Ettinger; Faeze Brahman; Sachin Kumar 009; Niloofar Mireshghallah; Ximing Lu; Maarten Sap; Yejin Choi 001; Nouha Dziri (NeurIPS, 2024)

RewardBench: Evaluating Reward Models for Language Modeling. - Nathan Lambert 001; Valentina Pyatkin; Jacob Morrison; LJ Miranda; Bill Yuchen Lin; Khyathi Raghavi Chandu; Nouha Dziri; Sachin Kumar 009; Tom Zick; Yejin Choi 001; Noah A. Smith; Hannaneh Hajishirzi (CoRR, 2024)

MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization. - Orevaoghene Ahia; Sachin Kumar 009; Hila Gonen; Valentin Hoffman; Tomasz Limisiewicz; Yulia Tsvetkov; Noah A. Smith (CoRR, 2024)

Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback. - Lester James Validad Miranda; Yizhong Wang; Yanai Elazar; Sachin Kumar 009; Valentina Pyatkin; Faeze Brahman; Noah A. Smith; Hannaneh Hajishirzi; Pradeep Dasigi (ACL (1), 2025)

Steering off Course: Reliability Challenges in Steering Language Models. - Patrick Queiroz Da Silva; Hari Sethuraman; Dheeraj Rajagopal; Hannaneh Hajishirzi; Sachin Kumar 009 (ACL (1), 2025)

ComPO: Community Preferences for Language Model Personalization. - Sachin Kumar 009; Chan Young Park; Yulia Tsvetkov; Noah A. Smith; Hannaneh Hajishirzi (NAACL (Long Papers), 2025)

RewardBench: Evaluating Reward Models for Language Modeling. - Nathan Lambert 001; Valentina Pyatkin; Jacob Morrison; Lester James V. Miranda; Bill Yuchen Lin; Khyathi Raghavi Chandu; Nouha Dziri; Sachin Kumar 009; Tom Zick; Yejin Choi 001; Noah A. Smith; Hannaneh Hajishirzi (NAACL (Findings), 2025)

BLAB: Brutally Long Audio Bench. - Orevaoghene Ahia; Martijn Bartelds; Kabir Ahuja; Hila Gonen; Valentin Hofmann; Siddhant Arora; Shuyue Stella Li; Vishal Puttagunta; Mofetoluwa Adeyemi; Charishma Buchireddy; Ben Walls; Noah Bennett; et al. (CoRR, 2025)