{"total":46,"rows":[{"id":"2108.00573","title":"MuSiQue: Multihop Questions via Single-hop Question Composition","created":"2021-08-02","cited_by_count":916,"area":null},{"id":"2201.08164","title":"From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI","created":"2022-01-20","cited_by_count":302,"area":null},{"id":"2110.01167","title":"Trustworthy AI: From Principles to Practices","created":"2021-10-04","cited_by_count":207,"area":null},{"id":"2301.04883","title":"SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images","created":"2023-01-12","cited_by_count":179,"area":null},{"id":"2104.07302","title":"TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graph","created":"2021-04-15","cited_by_count":60,"area":null},{"id":"2308.08973","title":"End-to-End Beam Retrieval for Multi-Hop Question Answering","created":"2023-08-17","cited_by_count":35,"area":null},{"id":"2103.11072","title":"Local Interpretations for Explainable Natural Language Processing: A Survey","created":"2021-03-20","cited_by_count":31,"area":null},{"id":"2111.11297","title":"Teaching Humans When To Defer to a Classifier via Exemplars","created":"2021-11-22","cited_by_count":29,"area":null},{"id":"2106.00920","title":"DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues","created":"2021-06-02","cited_by_count":25,"area":null},{"id":"2205.09226","title":"Modeling Multi-hop Question Answering as Single Sequence Prediction","created":"2022-05-18","cited_by_count":21,"area":null},{"id":"2104.04515","title":"Connecting Attributions and QA Model Behavior on Realistic Counterfactuals","created":"2021-04-09","cited_by_count":20,"area":null},{"id":"2105.11776","title":"Dynamic Semantic Graph Construction and Reasoning for Explainable Multi-hop Science Question Answering","created":"2021-05-25","cited_by_count":17,"area":null},{"id":"2211.14739","title":"MNER-QG: An End-to-End MRC framework for Multimodal Named Entity Recognition with Query Grounding","created":"2022-11-27","cited_by_count":16,"area":null},{"id":"2109.02905","title":"Exploiting Reasoning Chains for Multi-hop Science Question Answering","created":"2021-09-07","cited_by_count":15,"area":null},{"id":"2107.11823","title":"Graph-free Multi-hop Reading Comprehension: A Select-to-Guide Strategy","created":"2021-07-25","cited_by_count":13,"area":null},{"id":"2205.11729","title":"From Easy to Hard: Two-stage Selector and Reader for Multi-hop Question Answering","created":"2022-05-24","cited_by_count":12,"area":null},{"id":"2206.08486","title":"Interpretable AMR-Based Question Decomposition for Multi-hop Question Answering","created":"2022-06-16","cited_by_count":12,"area":null},{"id":"2103.12235","title":"Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization","created":"2021-03-22","cited_by_count":10,"area":null},{"id":"2109.06853","title":"Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension","created":"2021-09-14","cited_by_count":10,"area":null},{"id":"2203.17081","title":"Interpretation of Black Box NLP Models: A Survey","created":"2022-03-31","cited_by_count":9,"area":null},{"id":"2404.00897","title":"Machine Learning Robustness: A Primer","created":"2024-04-01","cited_by_count":8,"area":null},{"id":"2104.05861","title":"Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews","created":"2021-04-12","cited_by_count":7,"area":null},{"id":"2205.10059","title":"Beyond the Granularity: Multi-Perspective Dialogue Collaborative Selection for Dialogue State Tracking","created":"2022-05-20","cited_by_count":6,"area":null},{"id":"2511.17490","title":"Video-R4: Reinforcing Text-Rich Video Reasoning with Visual Rumination","created":"2025-11-21","cited_by_count":6,"area":null},{"id":"2101.05988","title":"Coarse-grained decomposition and fine-grained interaction for multi-hop question answering","created":"2021-01-15","cited_by_count":5,"area":null},{"id":"2109.10497","title":"A Simple Approach to Jointly Rank Passages and Select Relevant Sentences in the OBQA Context","created":"2021-09-22","cited_by_count":4,"area":null},{"id":"2112.09658","title":"Reasoning Chain Based Adversarial Attack for Multi-hop Question Answering","created":"2021-12-17","cited_by_count":4,"area":null},{"id":"2212.09512","title":"Rethinking Label Smoothing on Multi-hop Question Answering","created":"2022-12-19","cited_by_count":4,"area":null},{"id":"2402.19350","title":"Prompting Explicit and Implicit Knowledge for Multi-hop Question Answering Based on Human Reading Process","created":"2024-02-29","cited_by_count":4,"area":null},{"id":"2403.12678","title":"Empowering Air Travelers: A Chatbot for Canadian Air Passenger Rights","created":"2024-03-19","cited_by_count":4,"area":null},{"id":"2111.09029","title":"Towards Interpretable and Reliable Reading Comprehension: A Pipeline Model with Unanswerability Prediction","created":"2021-11-17","cited_by_count":3,"area":null},{"id":"2208.14001","title":"IMCI: Integrate Multi-view Contextual Information for Fact Extraction and Verification","created":"2022-08-30","cited_by_count":3,"area":null},{"id":"2209.06923","title":"Prompt-based Conservation Learning for Multi-hop Question Answering","created":"2022-09-14","cited_by_count":3,"area":null},{"id":"2104.08744","title":"Generative Context Pair Selection for Multi-hop Question Answering","created":"2021-04-18","cited_by_count":2,"area":null},{"id":"2107.00368","title":"Ensemble Learning-Based Approach for Improving Generalization Capability of Machine Reading Comprehension Systems","created":"2021-07-01","cited_by_count":2,"area":null},{"id":"2109.00077","title":"Interactive Machine Comprehension with Dynamic Knowledge Graphs","created":"2021-08-31","cited_by_count":2,"area":null},{"id":"2203.09073","title":"Ask to Understand: Question Generation for Multi-hop Question Answering","created":"2022-03-17","cited_by_count":2,"area":null},{"id":"2305.14815","title":"Machine Reading Comprehension using Case-based Reasoning","created":"2023-05-24","cited_by_count":2,"area":null},{"id":"2311.18151","title":"Uncertainty Guided Global Memory Improves Multi-Hop Question Answering","created":"2023-11-29","cited_by_count":2,"area":null},{"id":"2210.07126","title":"Challenges in Explanation Quality Evaluation","created":"2022-10-13","cited_by_count":1,"area":null},{"id":"2212.04072","title":"A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches","created":"2022-12-08","cited_by_count":1,"area":null},{"id":"2301.03765","title":"Cross-Model Comparative Loss for Enhancing Neuronal Utility in Language Understanding","created":"2023-01-10","cited_by_count":1,"area":null},{"id":"2110.07961","title":"Tracing Origins: Coreference-aware Machine Reading Comprehension","created":"2021-10-15","cited_by_count":0,"area":null},{"id":"2208.02169","title":"SpanDrop: Simple and Effective Counterfactual Learning for Long Sequences","created":"2022-08-03","cited_by_count":0,"area":null},{"id":"2210.02621","title":"U3E: Unsupervised and Erasure-based Evidence Extraction for Machine Reading Comprehension","created":"2022-10-06","cited_by_count":0,"area":null},{"id":"2311.02345","title":"Perturbation-based Active Learning for Question Answering","created":"2023-11-04","cited_by_count":0,"area":null}],"next_cursor":null}