{"url":"/task/value-prediction","name":"Value prediction","slug":"value-prediction","description_markdown":null,"categories":[{"name":"Computer Code","url":"/area/computer-code"},{"name":"Computer Vision","url":"/area/computer-vision"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":83,"papers_with_code":21,"benchmarks":1,"benchmark_tables_in_archive":1,"benchmark_tables_shown":1,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":1,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/value-prediction-on-py150-1","slug":"value-prediction-on-py150-1","dataset":"Py150","dataset_url":null,"rows_in_archive":1,"metrics":["MRR"],"first_row_in_archive_order":{"model":"DFSud","paper_title":"Code Prediction by Feeding Trees to Transformers","paper_url":"/paper/code-prediction-by-feeding-trees-to","paper_date":"2020-03-30","arxiv_id":"2003.13848","code_links":[{"title":"facebookresearch/code-prediction-transformer","url":"https://github.com/facebookresearch/code-prediction-transformer"}],"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":3}}}],"datasets":[],"subtasks":[{"url":"/task/body-mass-index-bmi-prediction","name":"Body Mass Index (BMI) Prediction"}],"parent_tasks":[{"url":"/task/program-synthesis","name":"Program Synthesis"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":21,"of":21,"tagged_in_all":83,"items":[{"url":"/paper/uncertainty-based-offline-reinforcement","title":"Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble","date":"2021-10-04","arxiv_id":"2110.01548","repositories_listed":5,"syntology":{"n":21,"n_ran":13,"n_unverified":8,"n_pointer_only":6}},{"url":"/paper/value-prediction-network","title":"Value Prediction Network","date":"2017-07-11","arxiv_id":"1707.03497","repositories_listed":2,"syntology":null},{"url":"/paper/shapley-guided-utility-learning-for-effective","title":"Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation","date":"2025-03-23","arxiv_id":"2503.18195","repositories_listed":1,"syntology":null},{"url":"/paper/personalized-federated-collaborative","title":"Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach","date":"2024-08-16","arxiv_id":"2408.08931","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_unverified":1,"n_pointer_only":6}},{"url":"/paper/end-to-end-syntax-score-prediction-benchmark","title":"CardioSyntax: end-to-end SYNTAX score prediction -- dataset, benchmark and method","date":"2024-07-29","arxiv_id":"2407.19894","repositories_listed":1,"syntology":null},{"url":"/paper/spatial-division-augmented-occupancy-field","title":"Spatial-Division Augmented Occupancy Field for Bone Shape Reconstruction from Biplanar X-Rays","date":"2024-07-22","arxiv_id":"2407.15433","repositories_listed":1,"syntology":null},{"url":"/paper/worldvaluesbench-a-large-scale-benchmark","title":"WorldValuesBench: A Large-Scale Benchmark Dataset for Multi-Cultural Value Awareness of Language Models","date":"2024-04-25","arxiv_id":"2404.16308","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_unverified":2,"n_pointer_only":5}},{"url":"/paper/supercompiler-code-optimization-with-zero","title":"CompilerDream: Learning a Compiler World Model for General Code Optimization","date":"2024-04-24","arxiv_id":"2404.16077","repositories_listed":1,"syntology":null},{"url":"/paper/extremecast-boosting-extreme-value-prediction","title":"ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast","date":"2024-02-02","arxiv_id":"2402.01295","repositories_listed":1,"syntology":null},{"url":"/paper/a-multi-granularity-aware-aspect-learning","title":"A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval","date":"2023-12-05","arxiv_id":"2312.02538","repositories_listed":1,"syntology":null},{"url":"/paper/spatiotemporal-graph-neural-networks-with","title":"Uncertainty-Aware Probabilistic Graph Neural Networks for Road-Level Traffic Accident Prediction","date":"2023-09-10","arxiv_id":"2309.05072","repositories_listed":1,"syntology":null},{"url":"/paper/reinforcement-learning-from-passive-data-via","title":"Reinforcement Learning from Passive Data via Latent Intentions","date":"2023-04-10","arxiv_id":"2304.04782","repositories_listed":1,"syntology":{"n":15,"n_ran":0,"n_unverified":15,"n_pointer_only":0}},{"url":"/paper/learning-fast-and-slow-a-goal-directed-memory","title":"Learning, Fast and Slow: A Goal-Directed Memory-Based Approach for Dynamic Environments","date":"2023-01-31","arxiv_id":"2301.13758","repositories_listed":1,"syntology":null},{"url":"/paper/on-the-estimation-bias-in-double-q-learning-1","title":"On the Estimation Bias in Double Q-Learning","date":"2021-09-29","arxiv_id":"2109.14419","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_unverified":2,"n_pointer_only":0}},{"url":"/paper/learning-state-representations-from-random","title":"Learning State Representations from Random Deep Action-conditional Predictions","date":"2021-02-09","arxiv_id":"2102.04897","repositories_listed":1,"syntology":null},{"url":"/paper/date-dual-attentive-tree-aware-embedding-for","title":"DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection","date":"2020-08-23","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/timexplain-a-framework-for-explaining-the","title":"timeXplain -- A Framework for Explaining the Predictions of Time Series Classifiers","date":"2020-07-15","arxiv_id":"2007.07606","repositories_listed":1,"syntology":{"n":10,"n_ran":0,"n_unverified":10,"n_pointer_only":0}},{"url":"/paper/piven-a-deep-neural-network-for-prediction","title":"PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction","date":"2020-06-09","arxiv_id":"2006.05139","repositories_listed":1,"syntology":null},{"url":"/paper/spatial-action-maps-for-mobile-manipulation","title":"Spatial Action Maps for Mobile Manipulation","date":"2020-04-20","arxiv_id":"2004.09141","repositories_listed":1,"syntology":{"n":8,"n_ran":2,"n_unverified":6,"n_pointer_only":0}},{"url":"/paper/ace-an-actor-ensemble-algorithm-for","title":"ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search","date":"2018-11-06","arxiv_id":"1811.02696","repositories_listed":1,"syntology":null},{"url":"/paper/treeqn-and-atreec-differentiable-tree","title":"TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning","date":"2017-10-31","arxiv_id":"1710.11417","repositories_listed":1,"syntology":{"n":12,"n_ran":0,"n_unverified":12,"n_pointer_only":0}}],"syntology_records":8,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}