Search Results for author: Keshav Singh

Found 11 papers, 5 papers with code

IRAC: A Domain-Specific Annotated Corpus of Implicit Reasoning in Arguments

1 code implementation LREC 2022 Keshav Singh, Naoya Inoue, Farjana Sultana Mim, Shoichi Naito, Kentaro Inui

To solve this problem, we hypothesize that as human reasoning is guided by innate collection of domain-specific knowledge, it might be beneficial to create such a domain-specific corpus for machines.

Exploring Methodologies for Collecting High-Quality Implicit Reasoning in Arguments

1 code implementation EMNLP (ArgMining) 2021 Keshav Singh, Farjana Sultana Mim, Naoya Inoue, Shoichi Naito, Kentaro Inui

Annotation of implicit reasoning (i. e., warrant) in arguments is a critical resource to train models in gaining deeper understanding and correct interpretation of arguments.

LPAttack: A Feasible Annotation Scheme for Capturing Logic Pattern of Attacks in Arguments

no code implementations LREC 2022 Farjana Sultana Mim, Naoya Inoue, Shoichi Naito, Keshav Singh, Kentaro Inui

Attacking is not always straightforward and often comprise complex rhetorical moves such that arguers might agree with a logic of an argument while attacking another logic.

TYPIC: A Corpus of Template-Based Diagnostic Comments on Argumentation

1 code implementation LREC 2022 Shoichi Naito, Shintaro Sawada, Chihiro Nakagawa, Naoya Inoue, Kenshi Yamaguchi, Iori Shimizu, Farjana Sultana Mim, Keshav Singh, Kentaro Inui

In this paper, we define three criteria that a template set should satisfy: expressiveness, informativeness, and uniqueness, and verify the feasibility of creating a template set that satisfies these criteria as a first trial.

Informativeness Slot Filling

Annotating Implicit Reasoning in Arguments with Causal Links

no code implementations26 Oct 2021 Keshav Singh, Naoya Inoue, Farjana Sultana Mim, Shoichi Naitoh, Kentaro Inui

Most of the existing work that focus on the identification of implicit knowledge in arguments generally represent implicit knowledge in the form of commonsense or factual knowledge.

An Analysis on Rate-Splitting Multiple Access for IRS Aided 6G Communication

no code implementations5 Jun 2021 Aditya Jolly, Sudip Biswas, Keshav Singh

Integrating intelligent reflecting surface (IRS) and Rate-Splitting Multiple Access (RSMA) is an effective solution to improve the spectral/energy efficiency in next-generation (beyond 5G (B5G) and 6G) wireless networks.

Multiple Antenna Selection and Successive Signal Detection for SM-based IRS-aided Communication

1 code implementation28 Apr 2021 Hasan Albinsaid, Keshav Singh, Ankur Bansal, Sudip Biswas, Chih-Peng Li, Zygmunt J. Haas

Intelligent reflecting surface (IRS) is being considered as a prospective candidate for next-generation wireless communication due to its ability to significantly improve coverage and spectral efficiency by controlling the propagation environment.

A Comparative Study on Collecting High-Quality Implicit Reasonings at a Large-scale

no code implementations16 Apr 2021 Keshav Singh, Paul Reisert, Naoya Inoue, Kentaro Inui

We construct a preliminary dataset of 6, 000 warrants annotated over 600 arguments for 3 debatable topics.

Natural Language Understanding

Block Deep Neural Network-Based Signal Detector for Generalized Spatial Modulation

2 code implementations8 Aug 2020 Hasan Albinsaid, Keshav Singh, Sudip Biswas, Chih-Peng Li, Mohamed-Slim Alouini

However, signal detection due to inter-channel interference among the active antennas is a challenge in GSM systems and is the focus of this letter.

Improving Evidence Detection by Leveraging Warrants

no code implementations WS 2019 Keshav Singh, Paul Reisert, Naoya Inoue, Pride Kavumba, Kentaro Inui

Recognizing the implicit link between a claim and a piece of evidence (i. e. warrant) is the key to improving the performance of evidence detection.

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