no code implementations • EMNLP 2020 • Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley
In this work, we perform the first large-scale analysis of discourse in media dialog and its impact on generative modeling of dialog turns, with a focus on interrogative patterns and use of external knowledge.
1 code implementation • 19 Aug 2023 • Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian McAuley
In this paper, we present empirical studies on conversational recommendation tasks using representative large language models in a zero-shot setting with three primary contributions.
no code implementations • 5 Jun 2023 • Myeongjun Jang, Bodhisattwa Prasad Majumder, Julian McAuley, Thomas Lukasiewicz, Oana-Maria Camburu
While recent works have been considerably improving the quality of the natural language explanations (NLEs) generated by a model to justify its predictions, there is very limited research in detecting and alleviating inconsistencies among generated NLEs.
no code implementations • 24 May 2023 • EunJeong Hwang, Bodhisattwa Prasad Majumder, Niket Tandon
An important aspect of developing LLMs that interact with humans is to align models' behavior to their users.
1 code implementation • 30 Mar 2023 • Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark
Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from LLMs through iterative feedback and refinement.
Ranked #6 on
Arithmetic Reasoning
on GSM8K
no code implementations • 14 Oct 2022 • Bodhisattwa Prasad Majumder, Zexue He, Julian McAuley
Debiasing methods in NLP models traditionally focus on isolating information related to a sensitive attribute (like gender or race).
no code implementations • 14 Oct 2022 • Zexue He, Yu Wang, Julian McAuley, Bodhisattwa Prasad Majumder
However, when sensitive information is semantically entangled with the task information of the input, e. g., gender information is predictive for a profession, a fair trade-off between task performance and bias mitigation is difficult to achieve.
no code implementations • 12 Sep 2022 • Zhouhang Xie, Julian McAuley, Bodhisattwa Prasad Majumder
Reviews contain rich information about product characteristics and user interests and thus are commonly used to boost recommender system performance.
no code implementations • 12 Sep 2022 • Zhouhang Xie, Sameer Singh, Julian McAuley, Bodhisattwa Prasad Majumder
Recent models can generate fluent and grammatical synthetic reviews while accurately predicting user ratings.
1 code implementation • ACL 2022 • Bodhisattwa Prasad Majumder, Harsh Jhamtani, Taylor Berg-Kirkpatrick, Julian McAuley
In this paper, we propose a post-hoc knowledge-injection technique where we first retrieve a diverse set of relevant knowledge snippets conditioned on both the dialog history and an initial response from an existing dialog model.
no code implementations • 9 Dec 2021 • Shuyang Li, Bodhisattwa Prasad Majumder, Julian McAuley
Conversational recommender systems offer the promise of interactive, engaging ways for users to find items they enjoy.
1 code implementation • Findings (EMNLP) 2021 • Zexue He, Bodhisattwa Prasad Majumder, Julian McAuley
Written language carries explicit and implicit biases that can distract from meaningful signals.
no code implementations • 25 Jun 2021 • Bodhisattwa Prasad Majumder, Oana-Maria Camburu, Thomas Lukasiewicz, Julian McAuley
Our framework improves over previous methods by: (i) reaching SOTA task performance while also providing explanations, (ii) providing two types of explanations, while existing models usually provide only one type, and (iii) beating by a large margin the previous SOTA in terms of quality of both types of explanations.
1 code implementation • ACL 2021 • Bodhisattwa Prasad Majumder, Taylor Berg-Kirkpatrick, Julian McAuley, Harsh Jhamtani
Humans often refer to personal narratives, life experiences, and events to make a conversation more engaging and rich.
1 code implementation • NAACL 2021 • Bodhisattwa Prasad Majumder, Sudha Rao, Michel Galley, Julian McAuley
The ability to generate clarification questions i. e., questions that identify useful missing information in a given context, is important in reducing ambiguity.
no code implementations • ACL (GEM) 2021 • Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Aremu Anuoluwapo, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna Clinciu, Dipanjan Das, Kaustubh D. Dhole, Wanyu Du, Esin Durmus, Ondřej Dušek, Chris Emezue, Varun Gangal, Cristina Garbacea, Tatsunori Hashimoto, Yufang Hou, Yacine Jernite, Harsh Jhamtani, Yangfeng Ji, Shailza Jolly, Mihir Kale, Dhruv Kumar, Faisal Ladhak, Aman Madaan, Mounica Maddela, Khyati Mahajan, Saad Mahamood, Bodhisattwa Prasad Majumder, Pedro Henrique Martins, Angelina McMillan-Major, Simon Mille, Emiel van Miltenburg, Moin Nadeem, Shashi Narayan, Vitaly Nikolaev, Rubungo Andre Niyongabo, Salomey Osei, Ankur Parikh, Laura Perez-Beltrachini, Niranjan Ramesh Rao, Vikas Raunak, Juan Diego Rodriguez, Sashank Santhanam, João Sedoc, Thibault Sellam, Samira Shaikh, Anastasia Shimorina, Marco Antonio Sobrevilla Cabezudo, Hendrik Strobelt, Nishant Subramani, Wei Xu, Diyi Yang, Akhila Yerukola, Jiawei Zhou
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics.
Ranked #1 on
Extreme Summarization
on GEM-XSum
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+5
1 code implementation • EMNLP 2020 • Bodhisattwa Prasad Majumder, Harsh Jhamtani, Taylor Berg-Kirkpatrick, Julian McAuley
Existing persona-grounded dialog models often fail to capture simple implications of given persona descriptions, something which humans are able to do seamlessly.
no code implementations • 7 Apr 2020 • Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley
Compared to existing large-scale proxies for conversational data, language models trained on our dataset exhibit better zero-shot out-of-domain performance on existing spoken dialog datasets, demonstrating its usefulness in modeling real-world conversations.
13 code implementations • 10 Mar 2020 • Thomas Bachlechner, Bodhisattwa Prasad Majumder, Huanru Henry Mao, Garrison W. Cottrell, Julian McAuley
Deep networks often suffer from vanishing or exploding gradients due to inefficient signal propagation, leading to long training times or convergence difficulties.
1 code implementation • IJCNLP 2019 • Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley
Existing approaches to recipe generation are unable to create recipes for users with culinary preferences but incomplete knowledge of ingredients in specific dishes.
Ranked #1 on
Recipe Generation
on Food.com
1 code implementation • IJCNLP 2019 • Huanru Henry Mao, Bodhisattwa Prasad Majumder, Julian McAuley, Garrison W. Cottrell
Stories generated with neural language models have shown promise in grammatical and stylistic consistency.
1 code implementation • CONLL 2018 • Amrith Krishna, Bodhisattwa Prasad Majumder, Rajesh Shreedhar Bhat, Pawan Goyal
We propose a post-OCR text correction approach for digitising texts in Romanised Sanskrit.
no code implementations • 29 Mar 2018 • Bodhisattwa Prasad Majumder, Aditya Subramanian, Abhinandan Krishnan, Shreyansh Gandhi, Ajinkya More
Extracting accurate attribute qualities from product titles is a vital component in delivering eCommerce customers with a rewarding online shopping experience via an enriched faceted search.
1 code implementation • 16 Oct 2016 • Bodhisattwa Prasad Majumder, Ayan Sengupta, Sajal jain, Parikshit Bhaduri
With the advancement of huge data generation and data handling capability, Machine Learning and Probabilistic modelling enables an immense opportunity to employ predictive analytics platform in high security critical industries namely data centers, electricity grids, utilities, airport etc.
1 code implementation • 28 Mar 2016 • Satrajit Mukherjee, Bodhisattwa Prasad Majumder, Aritran Piplai, Swagatam Das
The paper proposes a novel Kernelized image segmentation scheme for noisy images that utilizes the concept of Smallest Univalue Segment Assimilating Nucleus (SUSAN) and incorporates spatial constraints by computing circular colour map induced weights.