47 citations · 108 across the 13 of their papers we have counts for
14 papers
Beyond Performance: Quantifying and Mitigating Label Bias in LLMs
Yuval Reif, Roy Schwartz
Large language models (LLMs) have shown remarkable adaptability to diverse tasks, by leveraging context prompts containing instructions, or minimal input-output examples. However,…
Modeling Tag Prediction based on Question Tagging Behavior Analysis of CommunityQA Platform Users
Kuntal Kumar Pal, Michael Gamon, Nirupama Chandrasekaran +1
In community question-answering platforms, tags play essential roles in effective information organization and retrieval, better question routing, faster response to questions, and…
EDM3: Event Detection as Multi-task Text Generation
Ujjwala Anantheswaran, Himanshu Gupta, Mihir Parmar +2
Event detection refers to identifying event occurrences in a text and comprises of two subtasks; event identification and classification. We present EDM3, a novel approach for Even…
Prompt-Based Learning for Thread Structure Prediction in Cybersecurity Forums
Kazuaki Kashihara, Kuntal Kumar Pal, Chitta Baral +1
With recent trends indicating cyber crimes increasing in both frequency and cost, it is imperative to develop new methods that leverage data-rich hacker forums to assist in combati…
Exploring the Limits of Transfer Learning with Unified Model in the Cybersecurity Domain
Kuntal Kumar Pal, Kazuaki Kashihara, Ujjwala Anantheswaran +3
With the increase in cybersecurity vulnerabilities of software systems, the ways to exploit them are also increasing. Besides these, malware threats, irregular network interactions…
"John is 50 years old, can his son be 65?" Evaluating NLP Models' Understanding of Feasibility
Himanshu Gupta, Neeraj Varshney, Swaroop Mishra +5
In current NLP research, large-scale language models and their abilities are widely being discussed. Some recent works have also found notable failures of these models. Often these…
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi +37
How well can NLP models generalize to a variety of unseen tasks when provided with task instructions? To address this question, we first introduce Super-NaturalInstructions, a benc…
Constructing Flow Graphs from Procedural Cybersecurity Texts
Kuntal Kumar Pal, Kazuaki Kashihara, Pratyay Banerjee +3
Following procedural texts written in natural languages is challenging. We must read the whole text to identify the relevant information or identify the instruction flows to comple…
Variable Name Recovery in Decompiled Binary Code using Constrained Masked Language Modeling
Pratyay Banerjee, Kuntal Kumar Pal, Fish Wang +1
Decompilation is the procedure of transforming binary programs into a high-level representation, such as source code, for human analysts to examine. While modern decompilers can re…
Can Transformers Reason About Effects of Actions?
Pratyay Banerjee, Chitta Baral, Man Luo +4
A recent work has shown that transformers are able to "reason" with facts and rules in a limited setting where the rules are natural language expressions of conjunctions of conditi…
Natural Language QA Approaches using Reasoning with External Knowledge
Chitta Baral, Pratyay Banerjee, Kuntal Kumar Pal +1
Question answering (QA) in natural language (NL) has been an important aspect of AI from its early days. Winograd's ``councilmen'' example in his 1972 paper and McCarthy's Mr. Hug…
Knowledge Guided Named Entity Recognition for BioMedical Text
Pratyay Banerjee, Kuntal Kumar Pal, Murthy Devarakonda +1
In this work, we formulate the NER task as a multi-answer knowledge guided QA task (KGQA) which helps to predict entities only by assigning B, I and O tags without associating enti…
How Additional Knowledge can Improve Natural Language Commonsense Question Answering?
Arindam Mitra, Pratyay Banerjee, Kuntal Kumar Pal +2
Recently several datasets have been proposed to encourage research in Question Answering domains where commonsense knowledge is expected to play an important role. Recent language…
Careful Selection of Knowledge to solve Open Book Question Answering
Pratyay Banerjee, Kuntal Kumar Pal, Arindam Mitra +1
Open book question answering is a type of natural language based QA (NLQA) where questions are expected to be answered with respect to a given set of open book facts, and common kn…