Papers with Code 아카이브
Logical Reasoning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 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/yu-fangxu/for
공식 코드Flow of Reasoning:Training LLMs for Divergent Problem Solving with Minimal Examples
https://github.com/yuan-12138/mi-gpsr
공식 코드https://github.com/yuan-12138/vesnet-rl
공식 코드VesNet-RL: Simulation-based Reinforcement Learning for Real-World US Probe Navigation
https://github.com/yuantianyuan01/presight
공식 코드PreSight: Enhancing Autonomous Vehicle Perception with City-Scale NeRF Priors
https://github.com/yueshengbin/SMART
공식 코드Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks
https://github.com/yujunzhou/logical
공식 코드Dissecting Logical Reasoning in LLMs: A Fine-Grained Evaluation and Supervision Study
https://github.com/yuliang-liu/multimodalocr
공식 코드https://github.com/yunxinli/ndcr
공식 코드A Neural Divide-and-Conquer Reasoning Framework for Image Retrieval from Linguistically Complex Text
https://github.com/yushengzhao/td-stp
공식 코드Target-Driven Structured Transformer Planner for Vision-Language Navigation
https://github.com/yuweihao/reclor
공식 코드ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning
https://github.com/yuxichen25/memory-net-inverse
공식 코드Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems
https://github.com/yxKryptonite/OpenFMNav
공식 코드OpenFMNav: Towards Open-Set Zero-Shot Object Navigation via Vision-Language Foundation Models
https://github.com/yxbian23/aLLM4TS
공식 코드Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning
https://github.com/yxwan123/logicasker
공식 코드LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models
https://github.com/yxzwang/submissionverofyinyangnn
공식 코드Efficient Link Prediction via GNN Layers Induced by Negative Sampling
https://github.com/yyf17/saavn
공식 코드https://github.com/zanchangtong/unions
공식 코드Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation
https://github.com/zangir/llm-for-cp
공식 코드https://github.com/zavalab/plasmodata.jl
공식 코드PlasmoData.jl -- A Julia Framework for Modeling and Analyzing Complex Data as Graphs
https://github.com/zchuz/cot-reasoning-survey
공식 코드https://github.com/zd11024/NaviLLM
공식 코드https://github.com/zehao-wang/lad
공식 코드Layout-aware Dreamer for Embodied Referring Expression Grounding
https://github.com/zhang943/lpn-pytorch
공식 코드https://github.com/zhangpingrui/adaptive-text-dreamer
공식 코드Cross from Left to Right Brain: Adaptive Text Dreamer for Vision-and-Language Navigation
https://github.com/zhao-lab/kalidindi_dpgp_multi_vehicle_2019
공식 코드Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field
https://github.com/zhaorui-tan/L-Reg_NeurIPS24
공식 코드https://github.com/zhaozh10/ChatCAD
공식 코드ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Models
https://github.com/zhefan-xu/cerlab-uav-autonomy
공식 코드https://github.com/zhengkid/Truth_Table_Logical_Reasoning
공식 코드Learning to Reason via Mixture-of-Thought for Logical Reasoning
https://github.com/zhentingqi/rstar
공식 코드Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers
https://github.com/zhufengdaaa/soon
공식 코드SOON: Scenario Oriented Object Navigation with Graph-based Exploration
https://github.com/zhuochunli/learn-from-committee
공식 코드Learning from Committee: Reasoning Distillation from a Mixture of Teachers with Peer-Review
https://github.com/zihao-wang/number-nli
공식 코드A Neural-Symbolic Approach to Natural Language Understanding
https://github.com/zikuncshelly/gradctrl
공식 코드https://github.com/ziningzhu/adversarial_helpfulness
공식 코드LLM-Generated Black-box Explanations Can Be Adversarially Helpful
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.