Avishek Anand

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 139

Top Venues

Saarland University (PHD)

Education History

Saarland University

PHD

Publications

Lijun Lyu, Nirmal Roy, Harrie Oosterhuis, Avishek Anand
Is Interpretable Machine Learning Effective at Feature Selection for Neural Learning-to-Rank? CoRR (2024)
Abhijit Anand, Venktesh V, Vinay Setty, Avishek Anand
The Surprising Effectiveness of Rankers trained on Expanded Queries. SIGIR (2024)
Abhijit Anand, Jurek Leonhardt, Jaspreet Singh, Koustav Rudra, Avishek Anand
Data Augmentation for Sample Efficient and Robust Document Ranking. ACM Trans. Inf. Syst. 42 (5) (2024)
Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders. ACM Trans. Inf. Syst. 42 (5) (2024)
Maria Heuss, Maarten de Rijke, Avishek Anand
RankingSHAP - Listwise Feature Attribution Explanations for Ranking Models. CoRR (2024)
Jonas Wallat, Adam Jatowt, Avishek Anand
Temporal Blind Spots in Large Language Models. WSDM (2024)
Venktesh V, Deepali Prabhu, Avishek Anand
DEXTER: A Benchmark for open-domain Complex Question Answering using LLMs. CoRR (2024)
Lijun Lyu, Nirmal Roy, Harrie Oosterhuis, Avishek Anand
Is Interpretable Machine Learning Effective at Feature Selection for Neural Learning-to-Rank? ECIR (4) (2024)
Venktesh V, Abhijit Anand, Avishek Anand, Vinay Setty
QuanTemp: A real-world open-domain benchmark for fact-checking numerical claims. SIGIR (2024)
Abhijit Anand, Venktesh V, Vinay Setty, Avishek Anand
The Surprising Effectiveness of Rankers Trained on Expanded Queries. CoRR (2024)
Venktesh V, Abhijit Anand, Avishek Anand, Vinay Setty
NUMTEMP: A real-world benchmark to verify claims with statistical and temporal expressions. CoRR (2024)
Harrie Oosterhuis, Lijun Lyu, Avishek Anand
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions. CoRR (2024)
Lea Richtmann, Viktoria-S. Schmiesing, Dennis Wilken, Jan Heine, Aaron Tranter, Avishek Anand, Tobias J. Osborne, Michèle Heurs
Model-free reinforcement learning with noisy actions for automated experimental control in optics. CoRR (2024)
Jonas Wallat, Adam Jatowt, Avishek Anand
Temporal Blind Spots in Large Language Models. CoRR (2024)
Jurek Leonhardt, Koustav Rudra, Avishek Anand
Extractive Explanations for Interpretable Text Ranking. ACM Trans. Inf. Syst. 41 (4) (2023)
Venktesh V, Sourangshu Bhattacharya, Avishek Anand
In-Context Ability Transfer for Question Decomposition in Complex QA. CoRR (2023)
Lijun Lyu, Avishek Anand
Listwise Explanations for Ranking Models Using Multiple Explainers. ECIR (1) (2023)
Jonas Wallat, Fabian Beringer, Abhijit Anand, Avishek Anand
Probing BERT for Ranking Abilities. ECIR (2) (2023)
Thorben Funke, Megha Khosla, Mandeep Rathee, Avishek Anand
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35 (8) (2023)
Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
Efficient Neural Ranking using Forward Indexes and Lightweight Encoders. CoRR (2023)
Avishek Anand, Venktesh V, Abhijit Anand, Vinay Setty
Query Understanding in the Age of Large Language Models. CoRR (2023)
Abhijit Anand, Venktesh V, Vinay Setty, Avishek Anand
Context Aware Query Rewriting for Text Rankers using LLM. CoRR (2023)
Avishek Anand, Procheta Sen, Sourav Saha, Manisha Verma, Mandar Mitra
Explainable Information Retrieval. SIGIR (2023)
Jonas Wallat, Tianyi Zhang, Avishek Anand
The Effect of Masking Strategies on Knowledge Retention by Language Models. CoRR (2023)
Avishek Anand, Sourav Saha, Procheta Sen, Mandar Mitra
Explainability of Text Processing and Retrieval Methods. FIRE (2023)
Koustav Rudra, Zeon Trevor Fernando, Avishek Anand
An in-depth analysis of passage-level label transfer for contextual document ranking. Inf. Retr. J. 26 (1) (2023)
Simone Piaggesi, Megha Khosla, André Panisson, Avishek Anand
DINE: Dimensional Interpretability of Node Embeddings. CoRR (2023)
Avishek Anand, Maria Soledad Pera, Maria Heuss, Venktesh V, Matteo Corsi
Report on the 21st Dutch-Belgian Information Retrieval Workshop (DIR 2023). SIGIR Forum 57 (2) (2023)
Amir Abolfazli, Jakob Spiegelberg, Gregory Palmer, Avishek Anand
A Deep Reinforcement Learning Approach to Configuration Sampling Problem. ICDM (2023)
Abhijit Anand, Jurek Leonhardt, Jaspreet Singh, Koustav Rudra, Avishek Anand
Data Augmentation for Sample Efficient and Robust Document Ranking. CoRR (2023)
Zijian Zhang, Vinay Setty, Avishek Anand
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals. SIGIR (2022)
Zijian Zhang, Vinay Setty, Avishek Anand
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals. CoRR (2022)
Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
Efficient Neural Ranking using Forward Indexes. WWW (2022)
Yumeng Wang, Lijun Lyu, Avishek Anand
BERT Rankers are Brittle: A Study using Adversarial Document Perturbations. ICTIR (2022)
Peide Zhu, Zhen Wang, Claudia Hauff, Jie Yang, Avishek Anand
Answer Quality Aware Aggregation for Extractive QA Crowdsourcing. EMNLP (Findings) (2022)
Alexander Erlei, Richeek Das, Lukas Meub, Avishek Anand, Ujwal Gadiraju
For What It's Worth: Humans Overwrite Their Economic Self-interest to Avoid Bargaining With AI Systems. CHI (2022)
Avishek Anand, Lijun Lyu, Maximilian Idahl, Yumeng Wang, Jonas Wallat, Zijian Zhang
Explainable Information Retrieval: A Survey. CoRR (2022)
Abhijit Anand, Jurek Leonhardt, Koustav Rudra, Avishek Anand
Supervised Contrastive Learning Approach for Contextual Ranking. ICTIR (2022)
Yumeng Wang, Lijun Lyu, Avishek Anand
BERT Rankers are Brittle: a Study using Adversarial Document Perturbations. CoRR (2022)
Mandeep Rathee, Thorben Funke, Avishek Anand, Megha Khosla
BAGEL: A Benchmark for Assessing Graph Neural Network Explanations. CoRR (2022)
Abhijit Anand, Jurek Leonhardt, Koustav Rudra, Avishek Anand
Supervised Contrastive Learning Approach for Contextual Ranking. CoRR (2022)
Jurek Leonhardt, Marcel Jahnke, Avishek Anand
Distribution-Aligned Fine-Tuning for Efficient Neural Retrieval. CoRR (2022)
Zijian Zhang, Koustav Rudra, Avishek Anand
Explain and Predict, and then Predict Again. WSDM (2021)
Michael Völske, Alexander Bondarenko, Maik Fröbe, Matthias Hagen, Benno Stein, Jaspreet Singh, Avishek Anand
Towards Axiomatic Explanations for Neural Ranking Models. CoRR (2021)
Maximilian Idahl, Lijun Lyu, Ujwal Gadiraju, Avishek Anand
Towards Benchmarking the Utility of Explanations for Model Debugging. CoRR (2021)
Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
Fast Forward Indexes for Efficient Document Ranking. CoRR (2021)
Koustav Rudra, Zeon Trevor Fernando, Avishek Anand
An In-depth Analysis of Passage-Level Label Transfer for Contextual Document Ranking. CoRR (2021)
Jurek Leonhardt, Fabian Beringer, Avishek Anand
Exploiting Sentence-Level Representations for Passage Ranking. LWDA (2021)
Megha Khosla, Vinay Setty, Avishek Anand
A Comparative Study for Unsupervised Network Representation Learning. IEEE Trans. Knowl. Data Eng. 33 (5) (2021)
Mandeep Rathee, Zijian Zhang, Thorben Funke, Megha Khosla, Avishek Anand
Learnt Sparsification for Interpretable Graph Neural Networks. CoRR (2021)
Megha Khosla, Avishek Anand
Revisiting the Auction Algorithm for Weighted Bipartite Perfect Matchings. CoRR (2021)
Michael Völske, Alexander Bondarenko, Maik Fröbe, Benno Stein, Jaspreet Singh, Matthias Hagen, Avishek Anand
Towards Axiomatic Explanations for Neural Ranking Models. ICTIR (2021)
Jurek Leonhardt, Avishek Anand, Koustav Rudra
L3S at the TREC 2021 Deep Learning Track. TREC (2021)
Thorben Funke, Megha Khosla, Avishek Anand
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks. CoRR (2021)
Jonas Wallat, Jaspreet Singh, Avishek Anand
BERTnesia: Investigating the capture and forgetting of knowledge in BERT. CoRR (2021)
Jaspreet Singh, Megha Khosla, Zhenye Wang, Avishek Anand
Extracting per Query Valid Explanations for Blackbox Learning-to-Rank Models. ICTIR (2021)
Zijian Zhang, Koustav Rudra, Avishek Anand
FaxPlainAC: A Fact-Checking Tool Based on EXPLAINable Models with HumAn Correction in the Loop. CIKM (2021)
Jurek Leonhardt, Koustav Rudra, Avishek Anand
Learnt Sparsity for Effective and Interpretable Document Ranking. CoRR (2021)
Jurek Leonhardt, Fabian Beringer, Avishek Anand
Exploiting Sentence-Level Representations for Passage Ranking. CoRR (2021)
Zijian Zhang, Koustav Rudra, Avishek Anand
Explain and Predict, and then Predict again. CoRR (2021)
Zijian Zhang, Koustav Rudra, Avishek Anand
FaxPlainAC: A Fact-Checking Tool Based on EXPLAINable Models with HumAn Correction in the Loop. CoRR (2021)
Zijian Zhang, Jaspreet Singh, Ujwal Gadiraju, Avishek Anand
Dissonance Between Human and Machine Understanding. CoRR (2021)
Christian Otto, Matthias Springstein, Avishek Anand, Ralph Ewerth
Characterization and classification of semantic image-text relations. Int. J. Multim. Inf. Retr. 9 (1) (2020)
Jaspreet Singh, Avishek Anand
Model agnostic interpretability of rankers via intent modelling. FAT* (2020)
Jurek Leonhardt, Avishek Anand, Megha Khosla
Boilerplate Removal using a Neural Sequence Labeling Model. WWW (Companion Volume) (2020)
Rishiraj Saha Roy, Avishek Anand
Question Answering over Curated and Open Web Sources. CoRR (2020)
Rishiraj Saha Roy, Avishek Anand
Question Answering over Curated and Open Web Sources. ICTIR (2020)
Jonas Wallat, Jaspreet Singh, Avishek Anand
BERTnesia: Investigating the capture and forgetting of knowledge in BERT. CoRR (2020)
Koustav Rudra, Avishek Anand
Distant Supervision in BERT-based Adhoc Document Retrieval. CIKM (2020)
Jaspreet Singh, Megha Khosla, Avishek Anand
Valid Explanations for Learning to Rank Models. CoRR (2020)
Rishiraj Saha Roy, Avishek Anand
Question Answering over Curated and Open Web Sources. SIGIR (2020)
Avishek Anand, Lawrence Cavedon, Matthias Hagen, Hideo Joho, Mark Sanderson, Benno Stein
Dagstuhl seminar 19461 on conversational search: seminar goals and working group outcomes. SIGIR Forum 54 (1) (2020)
Jurek Leonhardt, Avishek Anand, Megha Khosla
Boilerplate Removal using a Neural Sequence Labeling Model. CoRR (2020)
Avishek Anand, Lawrence Cavedon, Matthias Hagen, Hideo Joho, Mark Sanderson, Benno Stein
Conversational Search - A Report from Dagstuhl Seminar 19461. CoRR (2020)
Jaspreet Singh, Jonas Wallat, Avishek Anand
BERTnesia: Investigating the capture and forgetting of knowledge in BERT. BlackboxNLP@EMNLP (2020)
Alexander Erlei, Franck Awounang Nekdem, Lukas Meub, Avishek Anand, Ujwal Gadiraju
Impact of Algorithmic Decision Making on Human Behavior: Evidence from Ultimatum Bargaining. HCOMP (2020)
Maximilian Idahl, Megha Khosla, Avishek Anand
Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases. CoRR (2019)
Besnik Fetahu, Avishek Anand, Maria Koutraki
TableNet: An Approach for Determining Fine-grained Relations for Wikipedia Tables. CoRR (2019)
Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand
Node Representation Learning for Directed Graphs. ECML/PKDD (1) (2019)
Avishek Anand, Lawrence Cavedon, Hideo Joho, Mark Sanderson, Benno Stein
Conversational Search (Dagstuhl Seminar 19461). Dagstuhl Reports 9 (11) (2019)
Besnik Fetahu, Avishek Anand, Maria Koutraki
TableNet: An Approach for Determining Fine-grained Relations for Wikipedia Tables. WWW (2019)
Megha Khosla, Avishek Anand, Vinay Setty
A Comprehensive Comparison of Unsupervised Network Representation Learning Methods. CoRR (2019)
Maximilian Idahl, Megha Khosla, Avishek Anand
Finding Interpretable Concept Spaces in Node Embeddings Using Knowledge Bases. PKDD/ECML Workshops (1) (2019)
Megha Khosla, Avishek Anand
A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs. Algorithmica 81 (9) (2019)
Zeon Trevor Fernando, Jaspreet Singh, Avishek Anand
A study on the Interpretability of Neural Retrieval Models using DeepSHAP. CoRR (2019)
Zijian Zhang, Jaspreet Singh, Ujwal Gadiraju, Avishek Anand
Dissonance Between Human and Machine Understanding. Proc. ACM Hum. Comput. Interact. 3 (CSCW) (2019)
Helge Holzmann, Avishek Anand, Megha Khosla
Estimating PageRank deviations in crawled graphs. Appl. Netw. Sci. 4 (1) (2019)
Zeon Trevor Fernando, Jaspreet Singh, Avishek Anand
A study on the Interpretability of Neural Retrieval Models using DeepSHAP. SIGIR (2019)
Christian Otto, Matthias Springstein, Avishek Anand, Ralph Ewerth
Understanding, Categorizing and Predicting Semantic Image-Text Relations. ICMR (2019)
Johannes Kiesel, Arefeh Bahrami, Benno Stein, Avishek Anand, Matthias Hagen
Clarifying False Memories in Voice-based Search. CHIIR (2019)
Jaspreet Singh, Avishek Anand
EXS: Explainable Search Using Local Model Agnostic Interpretability. WSDM (2019)
Avishek Anand, Megha Khosla, Jaspreet Singh, Jan-Hendrik Zab, Zijian Zhang
Asynchronous Training of Word Embeddings for Large Text Corpora. WSDM (2019)
Christian Otto, Matthias Springstein, Avishek Anand, Ralph Ewerth
Understanding, Categorizing and Predicting Semantic Image-Text Relations. CoRR (2019)
Jurek Leonhardt, Avishek Anand, Megha Khosla
User Fairness in Recommender Systems. WWW (Companion Volume) (2018)
Jaspreet Singh, Avishek Anand
Designing Search Tasks for Archive Search. CoRR (2018)
Jaspreet Singh, Avishek Anand
EXS: Explainable Search Using Local Model Agnostic Interpretability. CoRR (2018)
Jurek Leonhardt, Avishek Anand, Megha Khosla
User Fairness in Recommender Systems. CoRR (2018)
Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand
Node Representation Learning for Directed Graphs. CoRR (2018)
Jaspreet Singh, Avishek Anand
Posthoc Interpretability of Learning to Rank Models using Secondary Training Data. CoRR (2018)
Johannes Kiesel, Arefeh Bahrami, Benno Stein, Avishek Anand, Matthias Hagen
Toward Voice Query Clarification. SIGIR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Avishek Anand