Papers with Code 아카이브
Logical Reasoning
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- 10
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- 65
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/benywon/ReCO
공식 코드ReCO: A Large Scale Chinese Reading Comprehension Dataset on Opinion
https://github.com/bin123apple/macm
공식 코드MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
https://github.com/bio-ontology-research-group/mowl
공식 코드Ontology Embedding: A Survey of Methods, Applications and Resources
https://github.com/bioimage-io/bioimageio-chatbot
공식 코드BioImage.IO Chatbot: A Community-Driven AI Assistant for Integrative Computational Bioimaging
https://github.com/bkhmsi/llm-localization
공식 코드The LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant Units
https://github.com/bkuckuck/logical-skills-of-llms
공식 코드https://github.com/blackmit/comparing_graph_transformers_via_positional_encodings
공식 코드https://github.com/blcuicall/omgeval
공식 코드OMGEval: An Open Multilingual Generative Evaluation Benchmark for Large Language Models
https://github.com/bnediction/cegar-bonesis
공식 코드Tackling Universal Properties of Minimal Trap Spaces of Boolean Networks
https://github.com/bowen-upenn/llm_token_bias
공식 코드A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners
https://github.com/btfrontier/polygon_mapping
공식 코드Real-Time Polygonal Semantic Mapping for Humanoid Robot Stair Climbing
https://github.com/bubblybingbong/ekf
공식 코드Extended Kalman Filter State Estimation for Autonomous Competition Robots
https://github.com/bys0318/squire
공식 코드SQUIRE: A Sequence-to-sequence Framework for Multi-hop Knowledge Graph Reasoning
https://github.com/bytedance/omniscient-model
공식 코드Towards Open-Ended Visual Recognition with Large Language Model
https://github.com/candytalking/abdgen
공식 코드Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings
https://github.com/car-git/travelling-together
공식 코드https://github.com/carlosxcruzcode/compet_colab_sma_llm
공식 코드https://github.com/cather-chen/logical-reasoning-graph
공식 코드https://github.com/catherinehao/timetuner
공식 코드https://github.com/causalnlp/logical-fallacy
공식 코드https://github.com/cerebrasresearch/sift
공식 코드Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
https://github.com/cerebrasresearch/sparse-ift
공식 코드Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
https://github.com/chadlzx/nsp_qa
공식 코드A Neural-Symbolic Approach to Natural Language Understanding
https://github.com/chang-ml-thu/FGH-flow
공식 코드Understanding MCMC Dynamics as Flows on the Wasserstein Space
https://github.com/changhaonan/ovsg
공식 코드Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs
https://github.com/chen-judge/unigeo
공식 코드UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression
https://github.com/chenguolin/nutime
공식 코드NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining
https://github.com/chenjinyubuaa/sevol
공식 코드Reinforced Structured State-Evolution for Vision-Language Navigation
https://github.com/chenkang455/s-sdm
공식 코드SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams
https://github.com/chenmeiqii/teach-llm-lr
공식 코드Improving Large Language Models in Event Relation Logical Prediction
https://github.com/chenyingshu/advances_3d_neural_stylization
공식 코드https://github.com/chenyizi086/wu.2023.sigspatial
공식 코드Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical Maps
https://github.com/chiral-carbon/kg-for-science
공식 코드What's In Your Field? Mapping Scientific Research with Knowledge Graphs and Large Language Models
https://github.com/chiyusong/dynamics-of-instruction-tuning
공식 코드Dynamics of Instruction Tuning: Each Ability of Large Language Models Has Its Own Growth Pace
https://github.com/chongzhou96/maskclip
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.