https://github.com/microsoft/affectbased
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Papers with Code 아카이브
Logical Reasoning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 22
- 평가표
- 10
- 보존된 평가 기록
- 65
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/microsoft/rd-agent
https://github.com/microsoft/repoclassbench
https://github.com/minosworld/minos
MINOS: Multimodal Indoor Simulator for Navigation in Complex Environments
https://github.com/minstar/BIDAF
https://github.com/mirkozaff/aa-sgan
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
https://github.com/mit-acl/cadrl_ros
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning
https://github.com/mit-acl/gym-collision-avoidance
Socially Aware Motion Planning with Deep Reinforcement Learning
https://github.com/mit-acl/rl_collision_avoidance
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning
https://github.com/mjhucla/TF-mRNN
Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images
https://github.com/mlaico/fmow-helper
https://github.com/mobilellm/droidbot-gpt
https://github.com/montrealrobotics/one4all
https://github.com/morganmcg1/reformer-fastai
AutoTrans: Automating Transformer Design via Reinforced Architecture Search
https://github.com/morganmcg1/reformer-fastai-old
AutoTrans: Automating Transformer Design via Reinforced Architecture Search
https://github.com/muhdhuz/MTCRNN
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences
https://github.com/mxu34/DPGP
Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field
https://github.com/myyaqubpython/https-github.com-cq615-Deep-MRI-Reconstruction
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction
https://github.com/neurobot-project/AvoidanceSimulation
https://github.com/neurodram/3D-recurrent-visual-attention-model
NEURO-DRAM: a 3D recurrent visual attention model for interpretable neuroimaging classification
https://github.com/nicolay-r/reasoning-for-sentiment-analysis-framework
https://github.com/nigelyaoj/self-supervised-amodal-video-object-segmentation
https://github.com/nkluge-correa/teenytinyllama
https://github.com/nl2g/quarterly-arxiv
NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers?
https://github.com/nlp-uoregon/mlmm-evaluation
https://github.com/nolanwinsman/Team-Doom
https://github.com/nsavinov/SPTM
https://github.com/nutonomy/nuscenes-devkit
Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking
https://github.com/ollmer/mmlu
https://github.com/open-finance-lab/finlora
https://github.com/opendatalab/charm
https://github.com/opendatalab/pm4bench
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
https://github.com/opendilab/DI-engine
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
https://github.com/openlamm/lamm
Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models
https://github.com/opennlplab/transnormerllm
https://github.com/opscidia/science-checker
Science Checker Reloaded: A Bidirectional Paradigm for Transparency and Logical Reasoning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.