https://github.com/MrZihan/NavRAG
공식 코드NavRAG: Generating User Demand Instructions for Embodied Navigation through Retrieval-Augmented LLM
Papers with Code 아카이브
Logical Reasoning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MrZihan/Sim2Real-VLN-3DFF
공식 코드Sim-to-Real Transfer via 3D Feature Fields for Vision-and-Language Navigation
https://github.com/Mrmoore98/VectorMapNet_code
공식 코드https://github.com/MushroomHunting/RSS2020-online-domain-adaptation-pot
공식 코드https://github.com/MuyeHuang/VProChart
공식 코드https://github.com/MyChocer/KGTN
공식 코드https://github.com/NJUNLP/Knowledge-Free-Reasoning
공식 코드Large Language Models Are Cross-Lingual Knowledge-Free Reasoners
https://github.com/NVlabs/Bongard-LOGO
공식 코드Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning
https://github.com/NicolasAG/SGinPG
공식 코드Measuring Systematic Generalization in Neural Proof Generation with Transformers
https://github.com/OSU-NLP-Group/UGround
공식 코드Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents
https://github.com/OliverRichter/map-reader
공식 코드Teaching a Machine to Read Maps with Deep Reinforcement Learning
https://github.com/OpenBMB/CPO
공식 코드Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment
https://github.com/OpenDriveLab/MTGS
공식 코드https://github.com/PKU-YuanGroup/LLaVA-CoT
공식 코드https://github.com/PaulsonLab/MOBONS
공식 코드https://github.com/PortNLP/MultiWHO
공식 코드Who Relies More on World Knowledge and Bias for Syntactic Ambiguity Resolution: Humans or LLMs?
https://github.com/Priberam/mesinesp-svm
공식 코드Priberam at MESINESP Multi-label Classification of Medical Texts Task
https://github.com/PrimisAI/nexus
공식 코드Nexus: A Lightweight and Scalable Multi-Agent Framework for Complex Tasks Automation
https://github.com/RAIL-group/RAIL-group-software/tree/main/modules/lsp_gnn
공식 코드Improving Reliable Navigation under Uncertainty via Predictions Informed by Non-Local Information
https://github.com/RIET-lab/claim-compare
공식 코드ClaimCompare: A Data Pipeline for Evaluation of Novelty Destroying Patent Pairs
https://github.com/RU-Automated-Reasoning-Group/MUN
공식 코드https://github.com/Ram81/goat-bench
공식 코드https://github.com/RamyaKeerthy/Translation-NL2FOL
공식 코드https://github.com/RedwanNewaz/YoloTag
공식 코드YoloTag: Vision-based Robust UAV Navigation with Fiducial Markers
https://github.com/Rhoban/footstepnet_envs
공식 코드https://github.com/Rhyssiyan/DER-ClassIL.pytorch
공식 코드DER: Dynamically Expandable Representation for Class Incremental Learning
https://github.com/RobertTLange/action-grammars-hrl
공식 코드Semantic RL with Action Grammars: Data-Efficient Learning of Hierarchical Task Abstractions
https://github.com/Robinroy-peter/DRL-DynamicDroneLanding
공식 코드Lander.AI: Adaptive Landing Behavior Agent for Expertise in 3D Dynamic Platform Landings
https://github.com/RongKaiWeskerMA/INSTA
공식 코드Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
https://github.com/RussianNLP/TAPE
공식 코드https://github.com/SGPHD/E-Scooter_Rider_Detection
공식 코드E-Scooter Rider Detection and Classification in Dense Urban Environments
https://github.com/SafeyahShemali/LLM-Thematic-Fit-24
공식 코드Uncovering Autoregressive LLM Knowledge of Thematic Fit in Event Representation
https://github.com/SalesforceAIResearch/indict_code_gen
공식 코드INDICT: Code Generation with Internal Dialogues of Critiques for Both Security and Helpfulness
https://github.com/Scitator/Run-Skeleton-Run
공식 코드Run, skeleton, run: skeletal model in a physics-based simulation
https://github.com/SegwangKim/neural-seq2grid-module
공식 코드https://github.com/SeverTopan/SATNet
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.