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2020 – today
- 2023
[j8]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): 8687-8698 (2023)- [j7]Jurek Leonhardt, Koustav Rudra, Avishek Anand:
Extractive Explanations for Interpretable Text Ranking. ACM Trans. Inf. Syst. 41(4): 88:1-88:31 (2023) - [c62]Jonas Wallat, Fabian Beringer, Abhijit Anand, Avishek Anand:
Probing BERT for Ranking Abilities. ECIR (2) 2023: 255-273 - [c61]Lijun Lyu, Avishek Anand:
Listwise Explanations for Ranking Models Using Multiple Explainers. ECIR (1) 2023: 653-668 - [c60]Avishek Anand, Procheta Sen, Sourav Saha, Manisha Verma, Mandar Mitra:
Explainable Information Retrieval. SIGIR 2023: 3448-3451 - [i58]Jonas Wallat, Tianyi Zhang, Avishek Anand:
The Effect of Masking Strategies on Knowledge Retention by Language Models. CoRR abs/2306.07185 (2023) - [i57]Avishek Anand, Venktesh V, Abhijit Anand, Vinay Setty:
Query Understanding in the Age of Large Language Models. CoRR abs/2306.16004 (2023) - [i56]Abhijit Anand, Venktesh V, Vinay Setty, Avishek Anand:
Context Aware Query Rewriting for Text Rankers using LLM. CoRR abs/2308.16753 (2023) - [i55]Simone Piaggesi, Megha Khosla, André Panisson, Avishek Anand:
DINE: Dimensional Interpretability of Node Embeddings. CoRR abs/2310.01162 (2023) - [i54]Venktesh V, Sourangshu Bhattacharya, Avishek Anand:
In-Context Ability Transfer for Question Decomposition in Complex QA. CoRR abs/2310.18371 (2023) - [i53]Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand:
Efficient Neural Ranking using Forward Indexes and Lightweight Encoders. CoRR abs/2311.01263 (2023) - [i52]Abhijit Anand, Jurek Leonhardt, Jaspreet Singh, Koustav Rudra, Avishek Anand:
Data Augmentation for Sample Efficient and Robust Document Ranking. CoRR abs/2311.15426 (2023) - 2022
- [c59]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: 113:1-113:18 - [c58]Peide Zhu, Zhen Wang, Claudia Hauff, Jie Yang, Avishek Anand:
Answer Quality Aware Aggregation for Extractive QA Crowdsourcing. EMNLP (Findings) 2022: 6147-6159 - [c57]Abhijit Anand, Jurek Leonhardt, Koustav Rudra, Avishek Anand:
Supervised Contrastive Learning Approach for Contextual Ranking. ICTIR 2022: 61-71 - [c56]Yumeng Wang, Lijun Lyu, Avishek Anand:
BERT Rankers are Brittle: A Study using Adversarial Document Perturbations. ICTIR 2022: 115-120 - [c55]Zijian Zhang, Vinay Setty, Avishek Anand:
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals. SIGIR 2022: 3219-3223 - [c54]Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand:
Efficient Neural Ranking using Forward Indexes. WWW 2022: 266-276 - [i51]Zijian Zhang, Vinay Setty, Avishek Anand:
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals. CoRR abs/2205.01588 (2022) - [i50]Yumeng Wang, Lijun Lyu, Avishek Anand:
BERT Rankers are Brittle: a Study using Adversarial Document Perturbations. CoRR abs/2206.11724 (2022) - [i49]Mandeep Rathee, Thorben Funke, Avishek Anand, Megha Khosla:
BAGEL: A Benchmark for Assessing Graph Neural Network Explanations. CoRR abs/2206.13983 (2022) - [i48]Abhijit Anand, Jurek Leonhardt, Koustav Rudra, Avishek Anand:
Supervised Contrastive Learning Approach for Contextual Ranking. CoRR abs/2207.03153 (2022) - [i47]Avishek Anand, Lijun Lyu, Maximilian Idahl, Yumeng Wang, Jonas Wallat, Zijian Zhang:
Explainable Information Retrieval: A Survey. CoRR abs/2211.02405 (2022) - [i46]Jurek Leonhardt, Marcel Jahnke, Avishek Anand:
Distribution-Aligned Fine-Tuning for Efficient Neural Retrieval. CoRR abs/2211.04942 (2022) - 2021
- [b2]Rishiraj Saha Roy, Avishek Anand:
Question Answering for the Curated Web: Tasks and Methods in QA over Knowledge Bases and Text Collections. Synthesis Lectures on Information Concepts, Retrieval, and Services, Morgan & Claypool Publishers 2021, ISBN 978-3-031-79511-4, pp. 1-194 - [j6]Megha Khosla, Vinay Setty, Avishek Anand:
A Comparative Study for Unsupervised Network Representation Learning. IEEE Trans. Knowl. Data Eng. 33(5): 1807-1818 (2021) - [c53]Zijian Zhang, Koustav Rudra, Avishek Anand:
FaxPlainAC: A Fact-Checking Tool Based on EXPLAINable Models with HumAn Correction in the Loop. CIKM 2021: 4823-4827 - [c52]Michael Völske, Alexander Bondarenko, Maik Fröbe, Benno Stein, Jaspreet Singh, Matthias Hagen, Avishek Anand:
Towards Axiomatic Explanations for Neural Ranking Models. ICTIR 2021: 13-22 - [c51]Jaspreet Singh, Megha Khosla, Zhenye Wang, Avishek Anand:
Extracting per Query Valid Explanations for Blackbox Learning-to-Rank Models. ICTIR 2021: 203-210 - [c50]Jurek Leonhardt, Fabian Beringer, Avishek Anand:
Exploiting Sentence-Level Representations for Passage Ranking. LWDA 2021: 287-302 - [c49]Jurek Leonhardt, Avishek Anand, Koustav Rudra:
L3S at the TREC 2021 Deep Learning Track. TREC 2021 - [c48]Zijian Zhang, Koustav Rudra, Avishek Anand:
Explain and Predict, and then Predict Again. WSDM 2021: 418-426 - [i45]Zijian Zhang, Koustav Rudra, Avishek Anand:
Explain and Predict, and then Predict again. CoRR abs/2101.04109 (2021) - [i44]Megha Khosla, Avishek Anand:
Revisiting the Auction Algorithm for Weighted Bipartite Perfect Matchings. CoRR abs/2101.07155 (2021) - [i43]Zijian Zhang, Jaspreet Singh, Ujwal Gadiraju, Avishek Anand:
Dissonance Between Human and Machine Understanding. CoRR abs/2101.07337 (2021) - [i42]Koustav Rudra, Zeon Trevor Fernando, Avishek Anand:
An In-depth Analysis of Passage-Level Label Transfer for Contextual Document Ranking. CoRR abs/2103.16669 (2021) - [i41]Maximilian Idahl, Lijun Lyu, Ujwal Gadiraju, Avishek Anand:
Towards Benchmarking the Utility of Explanations for Model Debugging. CoRR abs/2105.04505 (2021) - [i40]Thorben Funke, Megha Khosla, Avishek Anand:
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks. CoRR abs/2105.08621 (2021) - [i39]Jonas Wallat, Jaspreet Singh, Avishek Anand:
BERTnesia: Investigating the capture and forgetting of knowledge in BERT. CoRR abs/2106.02902 (2021) - [i38]Jurek Leonhardt, Fabian Beringer, Avishek Anand:
Exploiting Sentence-Level Representations for Passage Ranking. CoRR abs/2106.07316 (2021) - [i37]Michael Völske, Alexander Bondarenko, Maik Fröbe, Matthias Hagen, Benno Stein, Jaspreet Singh, Avishek Anand:
Towards Axiomatic Explanations for Neural Ranking Models. CoRR abs/2106.08019 (2021) - [i36]Jurek Leonhardt, Koustav Rudra, Avishek Anand:
Learnt Sparsity for Effective and Interpretable Document Ranking. CoRR abs/2106.12460 (2021) - [i35]Mandeep Rathee, Zijian Zhang, Thorben Funke, Megha Khosla, Avishek Anand:
Learnt Sparsification for Interpretable Graph Neural Networks. CoRR abs/2106.12920 (2021) - [i34]Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand:
Fast Forward Indexes for Efficient Document Ranking. CoRR abs/2110.06051 (2021) - [i33]Zijian Zhang, Koustav Rudra, Avishek Anand:
FaxPlainAC: A Fact-Checking Tool Based on EXPLAINable Models with HumAn Correction in the Loop. CoRR abs/2110.10144 (2021) - 2020
- [j5]Christian Otto, Matthias Springstein, Avishek Anand, Ralph Ewerth:
Characterization and classification of semantic image-text relations. Int. J. Multim. Inf. Retr. 9(1): 31-45 (2020) - [j4]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): 3:1-3:11 (2020) - [c47]Jaspreet Singh, Jonas Wallat, Avishek Anand:
BERTnesia: Investigating the capture and forgetting of knowledge in BERT. BlackboxNLP@EMNLP 2020: 174-183 - [c46]Koustav Rudra, Avishek Anand:
Distant Supervision in BERT-based Adhoc Document Retrieval. CIKM 2020: 2197-2200 - [c45]Jaspreet Singh, Avishek Anand:
Model agnostic interpretability of rankers via intent modelling. FAT* 2020: 618-628 - [c44]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: 43-52 - [c43]Rishiraj Saha Roy, Avishek Anand:
Question Answering over Curated and Open Web Sources. ICTIR 2020: 193-194 - [c42]Rishiraj Saha Roy, Avishek Anand:
Question Answering over Curated and Open Web Sources. SIGIR 2020: 2432-2435 - [c41]Jurek Leonhardt, Avishek Anand, Megha Khosla:
Boilerplate Removal using a Neural Sequence Labeling Model. WWW (Companion Volume) 2020: 226-229 - [i32]Rishiraj Saha Roy, Avishek Anand:
Question Answering over Curated and Open Web Sources. CoRR abs/2004.11980 (2020) - [i31]Jaspreet Singh, Megha Khosla, Avishek Anand:
Valid Explanations for Learning to Rank Models. CoRR abs/2004.13972 (2020) - [i30]Jurek Leonhardt, Avishek Anand, Megha Khosla:
Boilerplate Removal using a Neural Sequence Labeling Model. CoRR abs/2004.14294 (2020) - [i29]Avishek Anand, Lawrence Cavedon, Matthias Hagen, Hideo Joho, Mark Sanderson, Benno Stein:
Conversational Search - A Report from Dagstuhl Seminar 19461. CoRR abs/2005.08658 (2020) - [i28]Jonas Wallat, Jaspreet Singh, Avishek Anand:
BERTnesia: Investigating the capture and forgetting of knowledge in BERT. CoRR abs/2010.09313 (2020)
2010 – 2019
- 2019
- [j3]Megha Khosla, Avishek Anand:
A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs. Algorithmica 81(9): 3707-3724 (2019) - [j2]Helge Holzmann, Avishek Anand, Megha Khosla:
Estimating PageRank deviations in crawled graphs. Appl. Netw. Sci. 4(1): 86:1-86:22 (2019) - [j1]Zijian Zhang, Jaspreet Singh, Ujwal Gadiraju, Avishek Anand:
Dissonance Between Human and Machine Understanding. Proc. ACM Hum. Comput. Interact. 3(CSCW): 56:1-56:23 (2019) - [c40]Johannes Kiesel, Arefeh Bahrami, Benno Stein, Avishek Anand, Matthias Hagen:
Clarifying False Memories in Voice-based Search. CHIIR 2019: 331-335 - [c39]Christian Otto, Matthias Springstein, Avishek Anand, Ralph Ewerth:
Understanding, Categorizing and Predicting Semantic Image-Text Relations. ICMR 2019: 168-176 - [c38]Maximilian Idahl, Megha Khosla, Avishek Anand:
Finding Interpretable Concept Spaces in Node Embeddings Using Knowledge Bases. PKDD/ECML Workshops (1) 2019: 229-240 - [c37]Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand:
Node Representation Learning for Directed Graphs. ECML/PKDD (1) 2019: 395-411 - [c36]Zeon Trevor Fernando, Jaspreet Singh, Avishek Anand:
A study on the Interpretability of Neural Retrieval Models using DeepSHAP. SIGIR 2019: 1005-1008 - [c35]Avishek Anand, Megha Khosla, Jaspreet Singh, Jan-Hendrik Zab, Zijian Zhang:
Asynchronous Training of Word Embeddings for Large Text Corpora. WSDM 2019: 168-176 - [c34]Jaspreet Singh, Avishek Anand:
EXS: Explainable Search Using Local Model Agnostic Interpretability. WSDM 2019: 770-773 - [c33]Besnik Fetahu, Avishek Anand, Maria Koutraki:
TableNet: An Approach for Determining Fine-grained Relations for Wikipedia Tables. WWW 2019: 2736-2742 - [i27]Besnik Fetahu, Avishek Anand, Maria Koutraki:
TableNet: An Approach for Determining Fine-grained Relations for Wikipedia Tables. CoRR abs/1902.01740 (2019) - [i26]Megha Khosla, Avishek Anand, Vinay Setty:
A Comprehensive Comparison of Unsupervised Network Representation Learning Methods. CoRR abs/1903.07902 (2019) - [i25]Christian Otto, Matthias Springstein, Avishek Anand, Ralph Ewerth:
Understanding, Categorizing and Predicting Semantic Image-Text Relations. CoRR abs/1906.08595 (2019) - [i24]Zeon Trevor Fernando, Jaspreet Singh, Avishek Anand:
A study on the Interpretability of Neural Retrieval Models using DeepSHAP. CoRR abs/1907.06484 (2019) - [i23]Maximilian Idahl, Megha Khosla, Avishek Anand:
Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases. CoRR abs/1910.05030 (2019) - [i22]Avishek Anand, Lawrence Cavedon, Hideo Joho, Mark Sanderson, Benno Stein:
Conversational Search (Dagstuhl Seminar 19461). Dagstuhl Reports 9(11): 34-83 (2019) - 2018
- [c32]Helge Holzmann, Avishek Anand, Megha Khosla:
Delusive PageRank in Incomplete Graphs. COMPLEX NETWORKS (1) 2018: 104-117 - [c31]Avishek Anand, Kilian Bizer, Alexander Erlei, Ujwal Gadiraju, Christian Heinze, Lukas Meub, Wolfgang Nejdl, Björn Steinrötter:
Effects of Algorithmic Decision-Making and Interpretability on Human Behavior: Experiments using Crowdsourcing. HCOMP (WIP&Demo) 2018 - [c30]Johannes Kiesel, Arefeh Bahrami, Benno Stein, Avishek Anand, Matthias Hagen:
Toward Voice Query Clarification. SIGIR 2018: 1257-1260 - [c29]Jurek Leonhardt, Avishek Anand, Megha Khosla:
User Fairness in Recommender Systems. WWW (Companion Volume) 2018: 101-102 - [i21]Jaspreet Singh, Avishek Anand:
Posthoc Interpretability of Learning to Rank Models using Secondary Training Data. CoRR abs/1806.11330 (2018) - [i20]Jurek Leonhardt, Avishek Anand, Megha Khosla:
User Fairness in Recommender Systems. CoRR abs/1807.06349 (2018) - [i19]Jaspreet Singh, Avishek Anand:
EXS: Explainable Search Using Local Model Agnostic Interpretability. CoRR abs/1809.03857 (2018) - [i18]Jaspreet Singh, Avishek Anand:
Interpreting search result rankings through intent modeling. CoRR abs/1809.05190 (2018) - [i17]Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand:
Node Representation Learning for Directed Graphs. CoRR abs/1810.09176 (2018) - [i16]Jaspreet Singh, Wolfgang Nejdl, Avishek Anand:
History by Diversity: Helping Historians search News Archives. CoRR abs/1810.10251 (2018) - [i15]Jaspreet Singh, Johannes Hoffart, Avishek Anand:
Discovering Entities with Just a Little Help from You. CoRR abs/1810.10252 (2018) - [i14]Jaspreet Singh, Avishek Anand:
Designing Search Tasks for Archive Search. CoRR abs/1810.10253 (2018) - [i13]Jaspreet Singh, Wolfgang Nejdl, Avishek Anand:
Expedition: A Time-Aware Exploratory Search System Designed for Scholars. CoRR abs/1810.10769 (2018) - [i12]Avishek Anand, Megha Khosla, Jaspreet Singh, Jan-Hendrik Zab, Zijian Zhang:
Asynchronous Training of Word Embeddings for Large Text Corpora. CoRR abs/1812.03825 (2018) - 2017
- [c28]Jaspreet Singh, Avishek Anand:
Designing Search Tasks for Archive Search. CHIIR 2017: 361-364 - [c27]Besnik Fetahu, Katja Markert, Avishek Anand:
Fine Grained Citation Span for References in Wikipedia. EMNLP 2017: 1990-1999 - [c26]Patrick Ernst, Arunav Mishra, Avishek Anand, Vinay Setty:
BioNex: A System For Biomedical News Event Exploration. SIGIR 2017: 1277-1280 - [c25]Helge Holzmann, Wolfgang Nejdl, Avishek Anand:
Exploring Web Archives Through Temporal Anchor Texts. WebSci 2017: 289-298 - [c24]Vinay Setty, Abhijit Anand, Arunav Mishra, Avishek Anand:
Modeling Event Importance for Ranking Daily News Events. WSDM 2017: 231-240 - [i11]Tuan Tran, Claudia Niederée, Nattiya Kanhabua, Ujwal Gadiraju, Avishek Anand:
Balancing Novelty and Salience: Adaptive Learning to Rank Entities for Timeline Summarization of High-impact Events. CoRR abs/1701.03947 (2017) - [i10]Helge Holzmann, Vinay Goel, Avishek Anand:
ArchiveSpark: Efficient Web Archive Access, Extraction and Derivation. CoRR abs/1702.01015 (2017) - [i9]Helge Holzmann, Avishek Anand:
Tempas: Temporal Archive Search Based on Tags. CoRR abs/1702.01076 (2017) - [i8]Helge Holzmann, Wolfgang Nejdl, Avishek Anand:
The Dawn of Today's Popular Domains: A Study of the Archived German Web over 18 Years. CoRR abs/1702.01151 (2017) - [i7]Helge Holzmann, Wolfgang Nejdl, Avishek Anand:
On the Applicability of Delicious for Temporal Search on Web Archives. CoRR abs/1702.01159 (2017) - [i6]Besnik Fetahu, Katja Markert, Wolfgang Nejdl, Avishek Anand:
Finding News Citations for Wikipedia. CoRR abs/1703.10339 (2017) - [i5]Besnik Fetahu, Katja Markert, Avishek Anand:
Automated News Suggestions for Populating Wikipedia Entity Pages. CoRR abs/1703.10344 (2017) - [i4]Besnik Fetahu, Abhijit Anand, Avishek Anand:
How much is Wikipedia Lagging Behind News? CoRR abs/1703.10345 (2017) - [i3]Besnik Fetahu, Katja Markert, Avishek Anand:
Fine Grained Citation Span for References in Wikipedia. CoRR abs/1707.07278 (2017) - 2016
- [c23]Jaspreet Singh, Wolfgang Nejdl, Avishek Anand:
History by Diversity: Helping Historians search News Archives. CHIIR 2016: 183-192 - [c22]Besnik Fetahu, Katja Markert, Wolfgang Nejdl, Avishek Anand:
Finding News Citations for Wikipedia. CIKM 2016: 337-346 - [c21]Jaspreet Singh, Johannes Hoffart, Avishek Anand:
Discovering Entities with Just a Little Help from You. CIKM 2016: 1331-1340 - [c20]Helge Holzmann, Wolfgang Nejdl, Avishek Anand:
The Dawn of Today's Popular Domains: A Study of the Archived German Web over 18 Years. JCDL 2016: 73-82 - [c19]Helge Holzmann, Vinay Goel, Avishek Anand:
ArchiveSpark: Efficient Web Archive Access, Extraction and Derivation. JCDL 2016: 83-92 - [c18]Zeon Trevor Fernando, Jaspreet Singh, Avishek Anand:
L3S at the NTCIR-12 Temporal Information Access (Temporalia-2) Task. NTCIR 2016 - [c17]Helge Holzmann, Wolfgang Nejdl, Avishek Anand:
On the Applicability of Delicious for Temporal Search on Web Archives. SIGIR 2016: 929-932 - [c16]Jaspreet Singh, Wolfgang Nejdl, Avishek Anand:
Expedition: A Time-Aware Exploratory Search System Designed for Scholars. SIGIR 2016: 1105-1108 - [c15]Nattiya Kanhabua, Avishek Anand:
Temporal Information Retrieval. SIGIR 2016: 1235-1238 - [c14]Avishek Anand, Jefferson Bailey:
Exploring the past of the web: alexandria & archive-it hackathon. WebSci 2016: 14 - [c13]Johannes Hoffart, Dragan Milchevski, Gerhard Weikum, Avishek Anand, Jaspreet Singh:
The Knowledge Awakens: Keeping Knowledge Bases Fresh with Emerging Entities. WWW (Companion Volume) 2016: 203-206 - [c12]Helge Holzmann, Avishek Anand:
Tempas: Temporal Archive Search Based on Tags. WWW (Companion Volume) 2016: 207-210 - [i2]Megha Khosla, Avishek Anand:
A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs. CoRR abs/1611.07786 (2016) - 2015
- [c11]Besnik Fetahu, Katja Markert, Avishek Anand:
Automated News Suggestions for Populating Wikipedia Entity Pages. CIKM 2015: 323-332 - [c10]Tuan Tran, Claudia Niederée, Nattiya Kanhabua, Ujwal Gadiraju, Avishek Anand:
Balancing Novelty and Salience: Adaptive Learning to Rank Entities for Timeline Summarization of High-impact Events. CIKM 2015: 1201-1210 - [c9]Evica Milchevski, Avishek Anand, Sebastian Michel:
The Sweet Spot between Inverted Indices and Metric-Space Indexing for Top-K-List Similarity Search. EDBT 2015: 253-264 - [c8]