https://github.com/teamcraft-bench/teamcraft
공식 코드TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft
Papers with Code 아카이브
Decision Making
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/teddykoker/u-noise
공식 코드U-Noise: Learnable Noise Masks for Interpretable Image Segmentation
https://github.com/tencent-ailab/rlogist
공식 코드RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning
https://github.com/tencent-ailab/tleague_projpage
공식 코드https://github.com/tengxiao1/DIL
공식 코드https://github.com/tengxiao1/gsil
공식 코드https://github.com/teosusnjak/survival-analysis-stage1
공식 코드https://github.com/teresalazar13/fairfeddrift
공식 코드Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning
https://github.com/tess022095/fair-automl
공식 코드Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML
https://github.com/teto1992/declace
공식 코드Continuous reasoning for adaptive container image distribution in the cloud-edge continuum
https://github.com/tetrzim/robust-probabilistic-forecasting
공식 코드https://github.com/tgangwani/BMIL
공식 코드Learning Belief Representations for Imitation Learning in POMDPs
https://github.com/tgangwani/RL-Indirect-imitation
공식 코드https://github.com/tgangwani/ailo
공식 코드Imitation Learning from Observations under Transition Model Disparity
https://github.com/thaole25/visualevaluativeai
공식 코드https://github.com/the-chen-lab/data-addition-dilemma
공식 코드https://github.com/the-finai/fincon
공식 코드https://github.com/theabrusch/freqrise
공식 코드https://github.com/theonesp/multimodal_mortality_covid
공식 코드https://github.com/theoverhelst/churn-uplift-dataset-paper
공식 코드A churn prediction dataset from the telecom sector: a new benchmark for uplift modeling
https://github.com/theoverhelst/uplift-predictive-paper
공식 코드https://github.com/theovincent/pbo
공식 코드https://github.com/theryanl/llm-rationality
공식 코드Large Language Models Assume People are More Rational than We Really are
https://github.com/theworldofagents/agentic-reasoning
공식 코드Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research
https://github.com/thibauttheate/risk-sensitive-policy-with-distributional-reinforcement-learning
공식 코드Risk-Sensitive Policy with Distributional Reinforcement Learning
https://github.com/thinklab-sjtu/predictiveco-benchmark
공식 코드Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime
https://github.com/thinklab-sjtu/rgm
공식 코드Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
https://github.com/thomasdengiz/Imitation_Learning_Weeks
공식 코드https://github.com/thu-bpm/reread
공식 코드Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting Evidence
https://github.com/thu-media/Comyco
공식 코드Comyco: Quality-Aware Adaptive Video Streaming via Imitation Learning
https://github.com/thu-rllab/lare
공식 코드Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning
https://github.com/thu-social-network-research-group/InvestAlign
공식 코드https://github.com/thudm/agentbench
공식 코드https://github.com/thudm/autowebglm
공식 코드AutoWebGLM: A Large Language Model-based Web Navigating Agent
https://github.com/thudm/t1
공식 코드Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
https://github.com/thuizhou/Collaborating-Networks
공식 코드Estimating Uncertainty Intervals from Collaborating Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.