{"total":18,"rows":[{"id":"2107.07651","title":"Align before Fuse: Vision and Language Representation Learning with Momentum Distillation","created":"2021-07-16","cited_by_count":1619,"area":null},{"id":"2102.12060","title":"Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processing","created":"2021-02-24","cited_by_count":126,"area":null},{"id":"2203.05081","title":"NLX-GPT: A Model for Natural Language Explanations in Vision and Vision-Language Tasks","created":"2022-03-09","cited_by_count":60,"area":null},{"id":"2106.11988","title":"On the Diversity and Limits of Human Explanations","created":"2021-06-22","cited_by_count":30,"area":null},{"id":"2211.12328","title":"A survey on knowledge-enhanced multimodal learning","created":"2022-11-19","cited_by_count":11,"area":null},{"id":"2207.00779","title":"FRAME: Evaluating Rationale-Label Consistency Metrics for Free-Text Rationales","created":"2022-07-02","cited_by_count":10,"area":null},{"id":"2208.04060","title":"GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training","created":"2022-08-08","cited_by_count":10,"area":null},{"id":"2609.25845","title":"Visual Jev: Accurate and Efficient Decisions from Shared Visual Context","created":"2026-09-22","cited_by_count":9,"area":null},{"id":"2310.14670","title":"Dataset Bias Mitigation in Multiple-Choice Visual Question Answering and Beyond","created":"2023-10-23","cited_by_count":7,"area":null},{"id":"2304.12443","title":"Understanding and Predicting Human Label Variation in Natural Language Inference through Explanation","created":"2023-04-24","cited_by_count":5,"area":null},{"id":"2604.02045","title":"BidirLM: From Text to Omnimodal Bidirectional Encoders by Adapting and Composing Causal LLMs","created":"2026-04-02","cited_by_count":5,"area":null},{"id":"2310.00503","title":"Black-box Attacks on Image Activity Prediction and its Natural Language Explanations","created":"2023-09-30","cited_by_count":1,"area":null},{"id":"2512.06814","title":"CAuSE: Decoding Multimodal Classifiers using Faithful Natural Language Explanation","created":"2025-12-07","cited_by_count":1,"area":null},{"id":"2106.14137","title":"Building a Video-and-Language Dataset with Human Actions for Multimodal Logical Inference","created":"2021-06-27","cited_by_count":0,"area":null},{"id":"2211.04946","title":"Accountable and Explainable Methods for Complex Reasoning over Text","created":"2022-11-09","cited_by_count":0,"area":null},{"id":"2511.17358","title":"Don't Learn, Ground: A Case for Natural Language Inference with Visual Grounding","created":"2025-11-21","cited_by_count":0,"area":null},{"id":"2603.18752","title":"WeNLEX: Weakly Supervised Natural Language Explanations for Multilabel Chest X-ray Classification","created":"2026-03-19","cited_by_count":0,"area":null},{"id":"2610.04792","title":"Do More Modalities Always Help? A Geometric Perspective on Missing-Modality Robustness","created":"2026-10-03","cited_by_count":0,"area":null}],"next_cursor":null}