Publications
Group highlights
More resources can be found here.
(For a full list see below or go to Google Scholar)
We introduce a new reasoning task and dataset of Logical fallacy detection.
Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea and Bernhard Schölkopf
We propose a probe model based on graph convolutions to interpret knowledge-enhanced LMs and understand what kind of knowledge is integrated into these models.
Yifan Hou, Guoji Fu and Mrinmaya Sachan
We propose kernel learning methods that increase the expressiveness of Efficient Transformers while keeping their complexity linear.
Sankalan Pal Chowdhury, Adamos Solomou, Avinava Dubey and Mrinmaya Sachan
We propose a probing approach that adapts the given task into a sentence completion format and performs probing using the built-in language modeling head.
Jiaoda Li, Ryan Cotterell and Mrinmaya Sachan
We propose a novel automatic metric to widen the scope of automatic MT evaluation from sentence to document level.
Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma, Dongdong Zhang, Jian Yang, Haoyang Huang, Rico Sennrich, Mrinmaya Sachan, Ryan Cotterell and Ming Zhou
We propose a structured model which directly learns to select an optimal set of spans for various span selection problems.
Tianyu Liu, Yuchen Eleanor Jiang, Ryan D Cotterell and Mrinmaya Sachan
We provide a causal analysis of the impact of translationese on Machine Translation performance.
Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan and Bernhard Schölkopf
We improve BERT’s robustness against word substitution attacks by leveraging self-supervised contrastive learning.
Zhao Meng, Yihan Dong, Mrinmaya Sachan and Roger Wattenhofer
We study language change through the lens of causality in order to model how various distributional factors causally effect language change
Daphna Keidar, Andreas Opedal, Zhijing Jin and Mrinmaya Sachan
We propose approaches to calibrate open-domain machine reading systems
Shehzaad Dhuliawala, Leonard Adolphs, Rajarshi Das and Mrinmaya Sachan
We propose a case-based reasoning approach to train agents and generalize efficiently out of the training distribution.
Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan and Mrinmaya Sachan
We jointly map contextualized text representations to a lower dimensional space and cluster them for syntax induction.
Vikram Gupta, Haoyue Shi, Kevin Gimpel and Mrinmaya Sachan
We investigate role of the process of data collection in NLP and explain it using causality.
Zhijing Jin, Julius von Kugelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan and Bernhard Schoelkopf
We introduce a dataset for literary pieces and their summaries together with descriptions of characters that appear in the texts.
Faeze Brahman, Meng Huang, Oyvind Tafjord, Chao Zhao, Mrinmaya Sachan and Snigdha Chaturvedi
We introduce a information-theoretic probe to detect if contextualized text representations encode information in linguistic graphs.
Yifan Hou and Mrinmaya Sachan
We introduce a coreference model which scales to documents of any length.
Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan and Andrew McCallum
We propose thinking frameworks to understand the direct and indirect real-world impact of NLP.
Zhijing Jin, Geeticka Chauhan, Brian Tse, Mrinmaya Sachan and Rada Mihalcea
We jointly map contextualized text representations to a lower dimensional space and cluster them for syntax induction.
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi,Kartik Talamadupula, Mrinmaya Sachan and Murray Campbell
We design new environments to test the ability of RL agents to utilize commonsense knowledge.
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan and Murray Campbell
We harvest structured knowledge of geometry from math textbooks.
Mrinmaya Sachan, Avinava Dubey, Eduard Hovy, Tom Mitchell, Dan Roth and Eric P. Xing
Computational Linguistics (CL) journal - Dec 2019 issue
We learn a pipeline process that incorporates existing code, pre-learned machine learning models, and human engineered rules.
Mrinmaya Sachan, Avinava Dubey, Tom Mitchell, Dan Roth and Eric P. Xing
We propose a meta-learning approach for universal NMT.
Emmanouil Antonios Platanios, Mrinmaya Sachan, Graham Neubig and Tom Mitchell
We learn to solve geometry problems by imitation demonstrations in textbooks.
Mrinmaya Sachan and Eric P. Xing
We propose a structured prediction approach to answer science questions in textbooks.
Mrinmaya Sachan, Avinava Dubey and Eric P. Xing
We propose an approach to answer reading comprehension questions using AMR graph representations.
Mrinmaya Sachan and Eric P. Xing
We propose a structured prediction approach to answer reading comprehension questions.
Mrinmaya Sachan, Avinava Dubey, Eric P. Xing and Matthew Richardson
Full List
Logical Fallacy Detection
Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea and Bernhard Schölkopf
arXiv:2202.13758
Understanding Knowledge Integration in Language Models with Graph Convolutions
Yifan Hou, Guoji Fu and Mrinmaya Sachan
arxiv:2202.00964
Learning the Transformer Kernel
Sankalan Pal Chowdhury, Adamos Solomou, Avinava Dubey and Mrinmaya Sachan
arXiv:2110.08323
Probing via Prompting
Jiaoda Li, Ryan Cotterell and Mrinmaya Sachan
NAACL 2022
BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation
Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma, Dongdong Zhang, Jian Yang, Haoyang Huang, Rico Sennrich, Mrinmaya Sachan, Ryan Cotterell and Ming Zhou
NAACL 2022
A Structured Span Selector
Tianyu Liu, Yuchen Eleanor Jiang, Ryan D Cotterell and Mrinmaya Sachan
NAACL 2022
Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance
Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan and Bernhard Schölkopf
NAACL 2022
Self-Supervised Contrastive Learning with Adversarial Perturbations for Robust Pretrained Language Models
Zhao Meng, Yihan Dong, Mrinmaya Sachan and Roger Wattenhofer
NAACL 2022 (Findings)
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang
Daphna Keidar, Andreas Opedal, Zhijing Jin and Mrinmaya Sachan
ACL 2022
Calibration of Machine Reading Systems at Scale
Shehzaad Dhuliawala, Leonard Adolphs, Rajarshi Das and Mrinmaya Sachan
ACL 2022 (Findings)
Case-based Reasoning for Better Generalization in Text-Adventure Games
Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan and Mrinmaya Sachan
ICLR (2022)
Deep Clustering of Text Representations for Supervision-free Probing of Syntax
Vikram Gupta, Haoyue Shi, Kevin Gimpel and Mrinmaya Sachan
AAAI (2022)
Causal Direction in Data Matters: Implications of Causal and Anticausal Learning in NLP
Zhijing Jin, Julius von Kugelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan and Bernhard Schoelkopf
EMNLP 2021
Let Your Characters Tell Their Story: A Dataset for Character-Centric Narrative Understanding
Faeze Brahman, Meng Huang, Oyvind Tafjord, Chao Zhao, Mrinmaya Sachan and Snigdha Chaturvedi
Findings of EMNLP 2021
Differentiable Subset Pruning of Transformer Heads
Jiaoda Li, Ryan Cotterell and Mrinmaya Sachan
TACL 2021
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach
Yifan Hou and Mrinmaya Sachan
ACL (2021)
Scaling Within Document Coreference for Long Texts
Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan and Andrew McCallum
Findings of ACL (2021)
How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact
Zhijing Jin, Geeticka Chauhan, Brian Tse, Mrinmaya Sachan and Rada Mihalcea
Findings of ACL (2021)
Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi,Kartik Talamadupula, Mrinmaya Sachan and Murray Campbell
ACL Short (2021)
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan and Murray Campbell
AAAI 2021
Stronger Transformers for Neural Multi-Hop Question Generation
Devendra Singh Sachan, Lingfei Wu, Mrinmaya Sachan and William Hamilton
arXiv:2010.11374 (2020)
Knowledge Graph Embedding Compression
Mrinmaya Sachan
ACL 2020
Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
Mrinmaya Sachan, Avinava Dubey, Eduard Hovy, Tom Mitchell, Dan Roth and Eric P. Xing
Computational Linguistics (CL) journal - Dec 2019 issue
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems
Mrinmaya Sachan, Avinava Dubey, Tom Mitchell, Dan Roth and Eric P. Xing
NeurIPS 2018
Parsing to Programs: A Framework for Situated QA
Mrinmaya Sachan and Eric P. Xing
KDD 2018
Self-Training for Jointly Learning to Ask and Answer Questions
Mrinmaya Sachan and Eric P. Xing
NAACL-HLT 2018
Contextual Parameter Generation for Universal Neural Machine Translation
Emmanouil Antonios Platanios, Mrinmaya Sachan, Graham Neubig and Tom Mitchell
EMNLP 2018
Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition
Devendra Singh Sachan, Pengtao Xie, Mrinmaya Sachan and Eric P. Xing
MLHC 2018
From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems
Mrinmaya Sachan, Avinava Dubey and Eric P. Xing
EMNLP 2017
Learning to Solve Geometry Problems from Natural Language Demonstrations in Textbooks
Mrinmaya Sachan and Eric P. Xing
StarSem 2017
Easy Questions First? A Case Study on Curriculum Learning for Question Answering.
Mrinmaya Sachan and Eric P. Xing
ACL 2016
Science Question Answering using Instructional Materials
Mrinmaya Sachan, Avinava Dubey and Eric P. Xing
ACL 2016 (Short)
Machine Comprehension using Rich Semantic Representations
Mrinmaya Sachan and Eric P. Xing
ACL 2016 (Short)
Learning Concept Taxonomies from Multi-modal Data
Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan and Eric P. Xing
ACL 2016
Grounding Topic Models with Knowledge Bases
Zhiting Hu, Gang Luo, Mrinmaya Sachan, Eric P. Xing and Zaiqing Nie
IJCAI 2016
Learning Answer-Entailing Structures for Machine Comprehension
Mrinmaya Sachan, Avinava Dubey, Eric P. Xing and Matthew Richardson
ACL 2015 (Outstanding paper)
An Active Learning Approach to Coreference Resolution.
Mrinmaya Sachan, Eduard H. Hovy and Eric P. Xing
IJCAI 2015