{"list":"other","total":51,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"2203.02155","title":"Training language models to follow instructions with human feedback","created":"2022-03-04","cited_by_count":15971},{"id":"2201.11903","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","created":"2022-01-28","cited_by_count":12459},{"id":"2110.14168","title":"Training Verifiers to Solve Math Word Problems","created":"2021-10-27","cited_by_count":10109},{"id":"2203.11171","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","created":"2022-03-21","cited_by_count":5708},{"id":"1706.04599","title":"On Calibration of Modern Neural Networks","created":"2017-06-14","cited_by_count":4960},{"id":"1801.01290","title":"Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor","created":"2018-01-04","cited_by_count":4885},{"id":"1803.10122","title":"World Models","created":"2018-03-27","cited_by_count":1513},{"id":"1806.01261","title":"Relational inductive biases, deep learning, and graph networks","created":"2018-06-04","cited_by_count":1360},{"id":"1705.05363","title":"Curiosity-driven Exploration by Self-supervised Prediction","created":"2017-05-15","cited_by_count":1194},{"id":"2301.08243","title":"Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture","created":"2023-01-19","cited_by_count":1039},{"id":"2007.04612","title":"Concept Bottleneck Models","created":"2020-07-09","cited_by_count":1032},{"id":"2112.00114","title":"Show Your Work: Scratchpads for Intermediate Computation with Language Models","created":"2021-11-30","cited_by_count":886},{"id":"1703.02910","title":"Deep Bayesian Active Learning with Image Data","created":"2017-03-08","cited_by_count":819},{"id":"2506.09985","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","created":"2025-06-11","cited_by_count":809},{"id":"2202.11214","title":"FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators","created":"2022-02-22","cited_by_count":776},{"id":"1802.08219","title":"Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds","created":"2018-02-22","cited_by_count":746},{"id":"1606.01868","title":"Unifying Count-Based Exploration and Intrinsic Motivation","created":"2016-06-06","cited_by_count":639},{"id":"2304.05376","title":"ChemCrow: Augmenting large-language models with chemistry tools","created":"2023-04-11","cited_by_count":631},{"id":"1706.08566","title":"SchNet: A continuous-filter convolutional neural network for modeling quantum interactions","created":"2017-06-26","cited_by_count":571},{"id":"2501.04227","title":"Agent Laboratory: Using LLM Agents as Research Assistants","created":"2025-01-08","cited_by_count":425},{"id":"2006.14779","title":"Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance","created":"2020-06-26","cited_by_count":399},{"id":"1904.12584","title":"The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision","created":"2019-04-26","cited_by_count":372},{"id":"2010.09885","title":"ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction","created":"2020-10-19","cited_by_count":337},{"id":"1911.10500","title":"Causality for Machine Learning","created":"2019-11-24","cited_by_count":243},{"id":"1711.05851","title":"Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning","created":"2017-11-15","cited_by_count":161},{"id":"2405.12209","title":"MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark","created":"2024-05-20","cited_by_count":105},{"id":"2406.06769","title":"DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents","created":"2024-06-10","cited_by_count":100},{"id":"2303.00980","title":"Learning to Grow Pretrained Models for Efficient Transformer Training","created":"2023-03-02","cited_by_count":83},{"id":"2411.00081","title":"PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks","created":"2024-10-31","cited_by_count":82},{"id":"2503.08979","title":"Agentic AI for Scientific Discovery: A Survey of Progress, Challenges, and Future Directions","created":"2025-03-12","cited_by_count":77},{"id":"2402.04268","title":"ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learning","created":"2024-01-27","cited_by_count":64},{"id":"2401.06949","title":"ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization","created":"2024-01-13","cited_by_count":61},{"id":"1412.2309","title":"Visual Causal Feature Learning","created":"2014-12-07","cited_by_count":59},{"id":"2312.10527","title":"CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems","created":"2023-12-16","cited_by_count":56},{"id":"2407.09811","title":"CellAgent: An LLM-driven Multi-Agent Framework for Automated Single-cell Data Analysis","created":"2024-07-13","cited_by_count":39},{"id":"2302.04869","title":"Reversible Vision Transformers","created":"2023-02-09","cited_by_count":33},{"id":"2401.17244","title":"LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation","created":"2024-01-30","cited_by_count":32},{"id":"2312.01291","title":"Opportunities for Retrieval and Tool Augmented Large Language Models in Scientific Facilities","created":"2023-12-03","cited_by_count":27},{"id":"2309.01038","title":"Neurosymbolic Reinforcement Learning and Planning: A Survey","created":"2023-09-02","cited_by_count":24},{"id":"2312.06902","title":"Reducing Energy Bloat in Large Model Training","created":"2023-12-12","cited_by_count":22},{"id":"2405.17044","title":"Generating Interesting Scientific Ideas using Knowledge Graphs and LLMs: Evaluations with 100 Research Group Leaders","created":"2024-05-27","cited_by_count":22},{"id":"1605.09370","title":"Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data","created":"2016-05-30","cited_by_count":20},{"id":"2011.06317","title":"Learning causal representations for robust domain adaptation","created":"2020-11-12","cited_by_count":18},{"id":"2409.05890","title":"Automating the Practice of Science -- Opportunities, Challenges, and Implications","created":"2024-08-27","cited_by_count":18},{"id":"2503.13503","title":"SciHorizon: Benchmarking AI-for-Science Readiness from Scientific Data to Large Language Models","created":"2025-03-12","cited_by_count":15},{"id":"2307.07522","title":"The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence","created":"2023-07-09","cited_by_count":12},{"id":"2502.13025","title":"Agentic Deep Graph Reasoning Yields Self-Organizing Knowledge Networks","created":"2025-02-18","cited_by_count":12},{"id":"2501.08120","title":"In-situ graph reasoning and knowledge expansion using Graph-PReFLexOR","created":"2025-01-14","cited_by_count":11},{"id":"2504.18687","title":"Transformational Creativity in Science: A Graphical Theory","created":"2025-04-25","cited_by_count":5},{"id":"2407.09093","title":"On Exact Bit-level Reversible Transformers Without Changing Architectures","created":"2024-07-12","cited_by_count":1}],"next_cursor":null}