no code implementations • FEVER (ACL) 2022 • Chieh-Yang Huang, Jinfeng Li, Nikita Bhutani, Alexander Whedon, Estevam Hruschka, Yoshi Suhara
To alleviate this scarcity problem, we develop an unsupervised method, ZL-Distiller, which leverages contextual language representations of the reviews and their distributional patterns to identify salient sentences about entities.
1 code implementation • Findings (NAACL) 2022 • Yutong Shao, Nikita Bhutani, Sajjadur Rahman, Estevam Hruschka
Entity set expansion (ESE) aims at obtaining a more complete set of entities given a textual corpus and a seed set of entities of a concept.
no code implementations • COLING 2022 • Sagnik Ray Choudhury, Nikita Bhutani, Isabelle Augenstein
We find that EP test results do not change significantly when the fine-tuned model performs well or in adversarial situations where the model is forced to learn wrong correlations.
1 code implementation • 21 Feb 2024 • Seiji Maekawa, Hayate Iso, Sairam Gurajada, Nikita Bhutani
We demonstrate the efficacy of our finer-grained metric and insights through an adaptive retrieval system that selectively employs retrieval and recall based on the frequencies of entities and relations in the question.
no code implementations • 2 Feb 2024 • Pouya Pezeshkpour, Eser Kandogan, Nikita Bhutani, Sajjadur Rahman, Tom Mitchell, Estevam Hruschka
We present a formal definition of reasoning capacity and illustrate its utility in identifying limitations within each component of the system.
1 code implementation • 10 Nov 2023 • Pouya Pezeshkpour, Hayate Iso, Thom Lake, Nikita Bhutani, Estevam Hruschka
We meticulously craft this benchmark to cater to a wide array of HR tasks, including matching and explaining resumes to job descriptions, extracting skills and experiences from resumes, and editing resumes.
1 code implementation • 20 Sep 2023 • Haopeng Zhang, Hayate Iso, Sairam Gurajada, Nikita Bhutani
Text editing is a crucial task of modifying text to better align with user intents.
1 code implementation • 14 Sep 2023 • Yunshu Wu, Hayate Iso, Pouya Pezeshkpour, Nikita Bhutani, Estevam Hruschka
Large Language Models (LLMs) have shown promising performance in summary evaluation tasks, yet they face challenges such as high computational costs and the Lost-in-the-Middle problem where important information in the middle of long documents is often overlooked.
no code implementations • 25 Aug 2023 • Vishwas Mruthyunjaya, Pouya Pezeshkpour, Estevam Hruschka, Nikita Bhutani
Despite these advancements, there is a void in comprehensively evaluating whether LMs can encompass the intricate topological and semantic attributes of KGs, attributes crucial for reasoning processes.
1 code implementation • 21 Dec 2022 • Bosung Kim, Hayate Iso, Nikita Bhutani, Estevam Hruschka, Ndapa Nakashole, Tom Mitchell
We propose a novel framework, ZETT (ZEro-shot Triplet extraction by Template infilling), that aligns the task objective to the pre-training objective of generative transformers to generalize to unseen relations.
Ranked #1 on Zero-shot Relation Triplet Extraction on FewRel
1 code implementation • NAACL 2022 • Farima Fatahi Bayat, Nikita Bhutani, H. V. Jagadish
Our experiments on CaRB and Wire57 datasets indicate that CompactIE finds 1. 5x-2x more compact extractions than previous systems, with high precision, establishing a new state-of-the-art performance in OpenIE.
Ranked #3 on Open Information Extraction on BenchIE
no code implementations • 15 Sep 2021 • Sagnik Ray Choudhury, Nikita Bhutani, Isabelle Augenstein
We find that EP test results do not change significantly when the fine-tuned model performs well or in adversarial situations where the model is forced to learn wrong correlations.
no code implementations • 23 Jul 2021 • Kameron B. Rodrigues, Shweta Khushu, Mukut Mukherjee, Andrew Banister, Anthony Hevia, Sampath Duddu, Nikita Bhutani
While many accept climate change and its growing impacts, few converse about it well, limiting the adoption speed of societal changes necessary to address it.
no code implementations • WS 2020 • Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish
Knowledge-based question answering (KB{\_}QA) has long focused on simple questions that can be answered from a single knowledge source, a manually curated or an automatically extracted KB.
1 code implementation • EMNLP 2020 • Johannes Bjerva, Nikita Bhutani, Behzad Golshan, Wang-Chiew Tan, Isabelle Augenstein
We find that subjectivity is also an important feature in the case of QA, albeit with more intricate interactions between subjectivity and QA performance.
1 code implementation • AKBC 2020 • Nikita Bhutani, Aaron Traylor, Chen Chen, Xiaolan Wang, Behzad Golshan, Wang-Chiew Tan
Since it can be expensive to obtain training data to learn to extract implications for each new domain of reviews, we propose an unsupervised KBC system, Sampo, Specifically, Sampo is tailored to build KBs for domains where many reviews on the same domain are available.
no code implementations • NAACL 2019 • Nikita Bhutani, Yoshihiko Suhara, Wang-Chiew Tan, Alon Halevy, H. V. Jagadish
We describe NeurON, a system for extracting tuples from question-answer pairs.
no code implementations • COLING 2018 • Nikita Bhutani, Kun Qian, Yunyao Li, H. V. Jagadish, Hern, Mauricio ez, Mitesh Vasa
We show that programs for mapping entity mentions to their structures can be automatically generated using human-comprehensible labels.