{"list":"other","total":52,"rows":[{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"2407.21783","title":"The Llama 3 Herd of Models","created":"2024-07-31","cited_by_count":14715},{"id":"2210.03629","title":"ReAct: Synergizing Reasoning and Acting in Language Models","created":"2022-10-06","cited_by_count":8695},{"id":"2210.02747","title":"Flow Matching for Generative Modeling","created":"2022-10-06","cited_by_count":5702},{"id":"2507.06261","title":"Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities","created":"2025-07-07","cited_by_count":3796},{"id":"2109.01652","title":"Finetuned Language Models Are Zero-Shot Learners","created":"2021-09-03","cited_by_count":3780},{"id":"2209.14988","title":"DreamFusion: Text-to-3D using 2D Diffusion","created":"2022-09-29","cited_by_count":3025},{"id":"2208.01626","title":"Prompt-to-Prompt Image Editing with Cross Attention Control","created":"2022-08-02","cited_by_count":2431},{"id":"2303.16634","title":"G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment","created":"2023-03-29","cited_by_count":2276},{"id":"2208.01618","title":"An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion","created":"2022-08-02","cited_by_count":2245},{"id":"2211.14730","title":"A Time Series is Worth 64 Words: Long-term Forecasting with Transformers","created":"2022-11-27","cited_by_count":2039},{"id":"2108.01073","title":"SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations","created":"2021-08-02","cited_by_count":1937},{"id":"2209.14792","title":"Make-A-Video: Text-to-Video Generation without Text-Video Data","created":"2022-09-29","cited_by_count":1742},{"id":"2110.08207","title":"Multitask Prompted Training Enables Zero-Shot Task Generalization","created":"2021-10-15","cited_by_count":1470},{"id":"2411.15594","title":"A Survey on LLM-as-a-Judge","created":"2024-11-23","cited_by_count":1423},{"id":"2205.10625","title":"Least-to-Most Prompting Enables Complex Reasoning in Large Language Models","created":"2022-05-21","cited_by_count":1407},{"id":"2211.01910","title":"Large Language Models Are Human-Level Prompt Engineers","created":"2022-11-03","cited_by_count":1045},{"id":"2210.03493","title":"Automatic Chain of Thought Prompting in Large Language Models","created":"2022-10-07","cited_by_count":688},{"id":"2210.11610","title":"Large Language Models Can Self-Improve","created":"2022-10-20","cited_by_count":664},{"id":"2210.11427","title":"DiffEdit: Diffusion-based semantic image editing with mask guidance","created":"2022-10-20","cited_by_count":647},{"id":"2210.03057","title":"Language Models are Multilingual Chain-of-Thought Reasoners","created":"2022-10-06","cited_by_count":530},{"id":"2110.05679","title":"Large Language Models Can Be Strong Differentially Private Learners","created":"2021-10-12","cited_by_count":412},{"id":"2210.00720","title":"Complexity-Based Prompting for Multi-Step Reasoning","created":"2022-10-03","cited_by_count":388},{"id":"2209.14610","title":"Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning","created":"2022-09-29","cited_by_count":350},{"id":"2205.09712","title":"Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning","created":"2022-05-19","cited_by_count":334},{"id":"2107.06383","title":"How Much Can CLIP Benefit Vision-and-Language Tasks?","created":"2021-07-13","cited_by_count":321},{"id":"2210.06280","title":"Language Models are Realistic Tabular Data Generators","created":"2022-10-12","cited_by_count":294},{"id":"2210.09150","title":"Prompting GPT-3 To Be Reliable","created":"2022-10-17","cited_by_count":260},{"id":"2101.10318","title":"Multi-Time Attention Networks for Irregularly Sampled Time Series","created":"2021-01-25","cited_by_count":238},{"id":"2301.12314","title":"Progressive Prompts: Continual Learning for Language Models","created":"2023-01-29","cited_by_count":197},{"id":"2207.00112","title":"Language model compression with weighted low-rank factorization","created":"2022-06-30","cited_by_count":195},{"id":"2110.03215","title":"Towards Continual Knowledge Learning of Language Models","created":"2021-10-07","cited_by_count":174},{"id":"2210.02441","title":"Ask Me Anything: A simple strategy for prompting language models","created":"2022-10-05","cited_by_count":155},{"id":"2110.05357","title":"Graph-Guided Network for Irregularly Sampled Multivariate Time Series","created":"2021-10-11","cited_by_count":111},{"id":"2011.00593","title":"MixKD: Towards Efficient Distillation of Large-scale Language Models","created":"2020-11-01","cited_by_count":65},{"id":"2406.16253","title":"LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing","created":"2024-06-24","cited_by_count":62},{"id":"2109.09774","title":"Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment","created":"2021-09-20","cited_by_count":53},{"id":"2303.00918","title":"STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables","created":"2023-03-02","cited_by_count":49},{"id":"2303.13664","title":"Temperature Schedules for Self-Supervised Contrastive Methods on Long-Tail Data","created":"2023-03-23","cited_by_count":44},{"id":"2205.14318","title":"Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions","created":"2022-05-28","cited_by_count":38},{"id":"2505.04966","title":"Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards","created":"2025-05-08","cited_by_count":34},{"id":"2302.13344","title":"Tailoring Language Generation Models under Total Variation Distance","created":"2023-02-26","cited_by_count":27},{"id":"2311.09497","title":"Peer Reviews of Peer Reviews: A Randomized Controlled Trial and Other Experiments","created":"2023-11-16","cited_by_count":27},{"id":"2502.17086","title":"Mind the Blind Spots: A Focus-Level Evaluation Framework for LLM Reviews","created":"2025-02-24","cited_by_count":24},{"id":"2311.11967","title":"Automatic Analysis of Substantiation in Scientific Peer Reviews","created":"2023-11-20","cited_by_count":19},{"id":"2011.15050","title":"A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences","created":"2020-11-30","cited_by_count":16},{"id":"2509.04484","title":"The Good, the Bad and the Constructive: Automatically Measuring Peer Review's Utility for Authors","created":"2025-08-31","cited_by_count":16},{"id":"2504.11042","title":"LazyReview A Dataset for Uncovering Lazy Thinking in NLP Peer Reviews","created":"2025-04-15","cited_by_count":13},{"id":"2503.21717","title":"CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?","created":"2025-03-27","cited_by_count":12},{"id":"2103.12170","title":"krippendorffsalpha: An R Package for Measuring Agreement Using Krippendorff's Alpha Coefficient","created":"2021-03-22","cited_by_count":7},{"id":"2110.01509","title":"DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models","created":"2021-10-04","cited_by_count":7},{"id":"2302.13331","title":"Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance","created":"2023-02-26","cited_by_count":2}],"next_cursor":null}