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Logical Reasoning
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sociam/liketrainer
공식 코드Like trainer, like bot? Inheritance of bias in algorithmic content moderation
https://github.com/some-random/theorem-proving-reasoning
공식 코드https://github.com/soroushmehr/sampleRNN_ICLR2017
공식 코드SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
https://github.com/sosppxo/3d-stmn
공식 코드https://github.com/sparkjiao/logicllm
공식 코드Exploring Self-supervised Logic-enhanced Training for Large Language Models
https://github.com/sparkjiao/merit
공식 코드MERIt: Meta-Path Guided Contrastive Learning for Logical Reasoning
https://github.com/sparkjiao/merit-v2
공식 코드Exploring Self-supervised Logic-enhanced Training for Large Language Models
https://github.com/srama2512/PONI
공식 코드PONI: Potential Functions for ObjectGoal Navigation with Interaction-free Learning
https://github.com/ssskj/evinet
공식 코드EviNet: Evidential Reasoning Network for Resilient Graph Learning in the Open and Noisy Environments
https://github.com/sstary/ssrs
공식 코드SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints
https://github.com/stable-lab/MAGE-A-Multi-Agent-Engine-for-Automated-RTL-Code-Generation
공식 코드MAGE: A Multi-Agent Engine for Automated RTL Code Generation
https://github.com/stanford-oval/genie-worksheets
공식 코드https://github.com/stanfordnlp/dspy
공식 코드Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs
https://github.com/steven-ccq/vilamp
공식 코드Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation
https://github.com/strawlab/msectrax
공식 코드https://github.com/strivin0311/long-llms-learning
공식 코드Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey
https://github.com/strong-ai-lab/abductionrules
공식 코드AbductionRules: Training Transformers to Explain Unexpected Inputs
https://github.com/strong-ai-lab/logical-and-abstract-reasoning
공식 코드https://github.com/strong-ai-lab/logical-equivalence-driven-amr-data-augmentation-for-representation-learning
공식 코드Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
https://github.com/suchanuchp/BrainTWT
공식 코드https://github.com/suhaisheng/robosense
공식 코드https://github.com/sunnynexus/webthinker
공식 코드WebThinker: Empowering Large Reasoning Models with Deep Research Capability
https://github.com/suzgunmirac/belief-in-the-machine
공식 코드Belief in the Machine: Investigating Epistemological Blind Spots of Language Models
https://github.com/suzgunmirac/meta-prompting
공식 코드Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding
https://github.com/svt-yang/medst
공식 코드Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training
https://github.com/sydney-machine-learning/deeplearning-decadalworldeconomy
공식 코드Recursive deep learning framework for forecasting the decadal world economic outlook
https://github.com/sysuselab/rustevo
공식 코드RustEvo^2: An Evolving Benchmark for API Evolution in LLM-based Rust Code Generation
https://github.com/tail-unica/ai-literacy-primary-ed
공식 코드A Structured Unplugged Approach for Foundational AI Literacy in Primary Education
https://github.com/tanfiona/LLM-on-Tabular-Data-Prediction-Table-Understanding-Data-Generation
공식 코드Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey
https://github.com/tankche1/Semantic-Feature-Augmentation-in-Few-shot-Learning
공식 코드Multi-level Semantic Feature Augmentation for One-shot Learning
https://github.com/tavisshore/BEV-CV
공식 코드BEV-CV: Birds-Eye-View Transform for Cross-View Geo-Localisation
https://github.com/tavisshore/PEnG
공식 코드https://github.com/tavisshore/SpaGBOL
공식 코드https://github.com/teacherpeterpan/logic-llm
공식 코드Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning
https://github.com/tedhuang96/mifwlstm
공식 코드Long-term Pedestrian Trajectory Prediction using Mutable Intention Filter and Warp LSTM
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