Search Results for author: Amit Awekar

Found 11 papers, 6 papers with code

Faster K-Means Cluster Estimation

1 code implementation17 Jan 2017 Siddhesh Khandelwal, Amit Awekar

We propose a fast heuristic to overcome this bottleneck with only marginal increase in MSE.

Clustering

Fine-grained Entity Recognition with Reduced False Negatives and Large Type Coverage

1 code implementation AKBC 2019 Abhishek Abhishek, Sanya Bathla Taneja, Garima Malik, Ashish Anand, Amit Awekar

Fine-grained Entity Recognition (FgER) is the task of detecting and classifying entity mentions to a large set of types spanning diverse domains such as biomedical, finance and sports.

Benchmarking

Decoding the Style and Bias of Song Lyrics

1 code implementation17 Jul 2019 Manash Pratim Barman, Amit Awekar, Sambhav Kothari

We focus on two aspects: style and biases of song lyrics.

Taxonomical hierarchy of canonicalized relations from multiple Knowledge Bases

1 code implementation13 Sep 2019 Akshay Parekh, Ashish Anand, Amit Awekar

Further, to address the second question, we canonicalize, filter, and combine the identified relations from the three resources to construct a taxonomical hierarchy.

Relation Relation Extraction

Collective Learning From Diverse Datasets for Entity Typing in the Wild

no code implementations20 Oct 2018 Abhishek Abhishek, Amar Prakash Azad, Balaji Ganesan, Ashish Anand, Amit Awekar

The CLF first creates a unified hierarchical label set (UHLS) and a label mapping by aggregating label information from all available datasets.

Entity Typing Sentence

Are Word Embedding Methods Stable and Should We Care About It?

no code implementations17 Apr 2021 Angana Borah, Manash Pratim Barman, Amit Awekar

A representation learning method is considered stable if it consistently generates similar representation of the given data across multiple runs.

Clustering Fairness +4

Budget Sensitive Reannotation of Noisy Relation Classification Data Using Label Hierarchy

no code implementations26 Dec 2021 Akshay Parekh, Ashish Anand, Amit Awekar

The immediate follow-up problem is: Given a specific reannotation budget, which subset of the data should we reannotate?

Relation Relation Classification

Noise in Relation Classification Dataset TACRED: Characterization and Reduction

no code implementations21 Nov 2023 Akshay Parekh, Ashish Anand, Amit Awekar

Towards the first objective, we analyze predictions and performance of state-of-the-art (SOTA) models to identify the root cause of noise in the dataset.

Classification Relation +1

Effect of dimensionality change on the bias of word embeddings

no code implementations28 Dec 2023 Rohit Raj Rai, Amit Awekar

First, there is a significant variation in the bias of word embeddings with the dimensionality change.

Word Embeddings

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