b'Avishek Anand'

research

∙ 08/31/2023

Context Aware Query Rewriting for Text Rankers using LLM

Query rewriting refers to an established family of approaches that are a...

0 Abhijit Anand, et al. ∙

research

∙ 06/28/2023

Query Understanding in the Age of Large Language Models

Querying, conversing, and controlling search and information-seeking int...

0 Avishek Anand, et al. ∙

research

∙ 06/12/2023

The Effect of Masking Strategies on Knowledge Retention by Language Models

Language models retain a significant amount of world knowledge from thei...

0 Jonas Wallat, et al. ∙

research

∙ 11/09/2022

Distribution-Aligned Fine-Tuning for Efficient Neural Retrieval

Dual-encoder-based neural retrieval models achieve appreciable performan...

0 Jurek Leonhardt, et al. ∙

research

∙ 11/04/2022

Explainable Information Retrieval: A Survey

Explainable information retrieval is an emerging research area aiming to...

0 Avishek Anand, et al. ∙

research

∙ 07/07/2022

Supervised Contrastive Learning Approach for Contextual Ranking

Contextual ranking models have delivered impressive performance improvem...

0 Abhijit Anand, et al. ∙

research

∙ 06/28/2022

BAGEL: A Benchmark for Assessing Graph Neural Network Explanations

The problem of interpreting the decisions of machine learning is a well-...

0 Mandeep Rathee, et al. ∙

research

∙ 06/23/2022

BERT Rankers are Brittle: a Study using Adversarial Document Perturbations

Contextual ranking models based on BERT are now well established for a w...

0 Yumeng Wang, et al. ∙

research

∙ 05/03/2022

SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals

We introduce SparcAssist, a general-purpose risk assessment tool for the...

0 Zijian Zhang, et al. ∙

research

∙ 10/12/2021

Fast Forward Indexes for Efficient Document Ranking

Neural approaches, specifically transformer models, for ranking document...

0 Jurek Leonhardt, et al. ∙

research

∙ 06/23/2021

Learnt Sparsification for Interpretable Graph Neural Networks

Graph neural networks (GNNs) have achieved great success on various task...

8 Mandeep Rathee, et al. ∙

research

∙ 06/23/2021

Learnt Sparsity for Effective and Interpretable Document Ranking

Machine learning models for the ad-hoc retrieval of documents and passag...

0 Jurek Leonhardt, et al. ∙

research

∙ 06/15/2021

Towards Axiomatic Explanations for Neural Ranking Models

Recently, neural networks have been successfully employed to improve upo...

0 Michael Völske, et al. ∙

research

∙ 06/14/2021

Exploiting Sentence-Level Representations for Passage Ranking

Recently, pre-trained contextual models, such as BERT, have shown to per...

0 Jurek Leonhardt, et al. ∙

research

∙ 05/18/2021

Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks

With the ever-increasing popularity and applications of graph neural net...

14 Thorben Funke, et al. ∙

research

∙ 05/10/2021

Towards Benchmarking the Utility of Explanations for Model Debugging

Post-hoc explanation methods are an important class of approaches that h...

0 Maximilian Idahl, et al. ∙

research

∙ 03/30/2021

An In-depth Analysis of Passage-Level Label Transfer for Contextual Document Ranking

Recently introduced pre-trained contextualized autoregressive models lik...

0 Koustav Rudra, et al. ∙

research

∙ 01/18/2021

Dissonance Between Human and Machine Understanding

Complex machine learning models are deployed in several critical domains...

11 Zijian Zhang, et al. ∙

research

∙ 01/18/2021

Revisiting the Auction Algorithm for Weighted Bipartite Perfect Matchings

We study the classical weighted perfect matchings problem for bipartite ...

0 Megha Khosla, et al. ∙

research

∙ 01/11/2021

Explain and Predict, and then Predict again

A desirable property of learning systems is to be both effective and int...

0 Zijian Zhang, et al. ∙

research

∙ 10/19/2020

BERTnesia: Investigating the capture and forgetting of knowledge in BERT

Probing complex language models has recently revealed several insights i...

9 Jonas Wallat, et al. ∙

research

∙ 05/18/2020

Conversational Search – A Report from Dagstuhl Seminar 19461

Dagstuhl Seminar 19461 "Conversational Search" was held on 10-15 Novembe...

0 Avishek Anand, et al. ∙

research

∙ 04/29/2020

Valid Explanations for Learning to Rank Models

Learning-to-rank (LTR) is a class of supervised learning techniques that...

22 Jaspreet Singh, et al. ∙

research

∙ 04/24/2020

Question Answering over Curated and Open Web Sources

The last few years have seen an explosion of research on the topic of au...

0 Rishiraj Saha Roy, et al. ∙

research

∙ 04/22/2020

Boilerplate Removal using a Neural Sequence Labeling Model

The extraction of main content from web pages is an important task for n...

0 Jurek Leonhardt, et al. ∙

research

∙ 10/11/2019

Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases

In this paper we propose and study the novel problem of explaining node ...

0 Maximilian Idahl, et al. ∙

research

∙ 07/15/2019

A study on the Interpretability of Neural Retrieval Models using DeepSHAP

A recent trend in IR has been the usage of neural networks to learn retr...

0 Zeon Trevor Fernando, et al. ∙

research

∙ 06/20/2019

Understanding, Categorizing and Predicting Semantic Image-Text Relations

Two modalities are often used to convey information in a complementary a...

0 Christian Otto, et al. ∙

research

∙ 03/19/2019

A Comprehensive Comparison of Unsupervised Network Representation Learning Methods

There has been appreciable progress in unsupervised network representati...

0 Megha Khosla, et al. ∙

research

∙ 02/05/2019

TableNet: An Approach for Determining Fine-grained Relations for Wikipedia Tables

Wikipedia tables represent an important resource, where information is o...

0 Besnik Fetahu, et al. ∙

research

∙ 12/07/2018

Asynchronous Training of Word Embeddings for Large Text Corpora

Word embeddings are a powerful approach for analyzing language and have ...

0 Avishek Anand, et al. ∙

research

∙ 10/25/2018

Expedition: A Time-Aware Exploratory Search System Designed for Scholars

Archives are an important source of study for various scholars. Digitiza...

0 Jaspreet Singh, et al. ∙

research

∙ 10/24/2018

Designing Search Tasks for Archive Search

Longitudinal corpora like legal, corporate and newspaper archives are of...

0 Jaspreet Singh, et al. ∙

research

∙ 10/24/2018

Discovering Entities with Just a Little Help from You

Linking entities like people, organizations, books, music groups and the...

0 Jaspreet Singh, et al. ∙

research

∙ 10/24/2018

History by Diversity: Helping Historians search News Archives

Longitudinal corpora like newspaper archives are of immense value to his...

0 Jaspreet Singh, et al. ∙

research

∙ 10/22/2018

Node Representation Learning for Directed Graphs

We propose a novel approach for learning node representations in directe...

0 Megha Khosla, et al. ∙

research

∙ 09/13/2018

Interpreting search result rankings through intent modeling

Given the recent interest in arguably accurate yet non-interpretable neu...

0 Jaspreet Singh, et al. ∙

research

∙ 09/11/2018

EXS: Explainable Search Using Local Model Agnostic Interpretability

Retrieval models in information retrieval are used to rank documents for...

0 Jaspreet Singh, et al. ∙

research

∙ 07/17/2018

User Fairness in Recommender Systems

Recent works in recommendation systems have focused on diversity in reco...

0 Jurek Leonhardt, et al. ∙

research

∙ 06/29/2018

Posthoc Interpretability of Learning to Rank Models using Secondary Training Data

Predictive models are omnipresent in automated and assisted decision mak...

0 Jaspreet Singh, et al. ∙

research

∙ 07/23/2017

Fine Grained Citation Span for References in Wikipedia

Verifiability is one of the core editing principles in Wikipedia, editor...

0 Besnik Fetahu, et al. ∙

research

∙ 03/30/2017

Automated News Suggestions for Populating Wikipedia Entity Pages

Wikipedia entity pages are a valuable source of information for direct c...

0 Besnik Fetahu, et al. ∙

research

∙ 03/30/2017

Finding News Citations for Wikipedia

An important editing policy in Wikipedia is to provide citations for add...

0 Besnik Fetahu, et al. ∙

research

∙ 02/03/2017

The Dawn of Today's Popular Domains: A Study of the Archived German Web over 18 Years

The Web has been around and maturing for 25 years. The popular websites ...

0 Helge Holzmann, et al. ∙

research

∙ 02/03/2017

ArchiveSpark: Efficient Web Archive Access, Extraction and Derivation

Web archives are a valuable resource for researchers of various discipli...

0 Helge Holzmann, et al. ∙

research

∙ 01/14/2017

Balancing Novelty and Salience: Adaptive Learning to Rank Entities for Timeline Summarization of High-impact Events

Long-running, high-impact events such as the Boston Marathon bombing oft...

0 Tuan Tran, et al. ∙

Avishek Anand

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