https://github.com/damo-nlp-sg/videollama3
공식 코드VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding
Papers with Code 아카이브
Philosophy
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/davidwhogg/BadForScience
공식 코드https://github.com/dcdmllm/healthgpt
공식 코드https://github.com/divelab/DIG
공식 코드FlowX: Towards Explainable Graph Neural Networks via Message Flows
https://github.com/dmelis/interpretwoe
공식 코드From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
https://github.com/duncanmcelfresh/indecision-modeling
공식 코드https://github.com/eduardacaldeira/mst-kd
공식 코드MST-KD: Multiple Specialized Teachers Knowledge Distillation for Fair Face Recognition
https://github.com/facebookresearch/soc-matching
공식 코드https://github.com/fanning-zhang/satnet
공식 코드Towards Top-Down Stereo Image Quality Assessment via Stereo Attention
https://github.com/farama-foundation/minigrid
공식 코드https://github.com/farama-foundation/miniworld
공식 코드https://github.com/francesco-sovrano/doxpy
공식 코드An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability
https://github.com/francesco-sovrano/from-philosophy-to-interfaces-an-explanatory-method-and-a-tool-inspired-by-achinstein-s-theory-of-e
공식 코드https://github.com/francesco-sovrano/yai4hu
공식 코드https://github.com/frankyu5666666/simpleunet
공식 코드Simple is what you need for efficient and accurate medical image segmentation
https://github.com/freedomintelligence/reasoningnlp
공식 코드https://github.com/fsoco/fsoco-devkit
공식 코드https://github.com/fub-hcc/ikon-backend
공식 코드https://github.com/fudan-zvg/bridgead
공식 코드Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
https://github.com/geox-lab/allspark
공식 코드https://github.com/goyalpike/quadratic-stable-opinf
공식 코드Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference
https://github.com/guojiajeremy/dinomaly
공식 코드Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
https://github.com/helsinki-nlp/mammoth
공식 코드MAMMOTH: Massively Multilingual Modular Open Translation @ Helsinki
https://github.com/hltchkust/cantonese-asr
공식 코드Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset
https://github.com/howiehwong/awareness-in-llm
공식 코드I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench
https://github.com/hqucv/dmtrack
공식 코드Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy
https://github.com/hslyu/gif
공식 코드Deeper Understanding of Black-box Predictions via Generalized Influence Functions
https://github.com/huangd1999/bort
공식 코드Two Heads are Better than One: Robust Learning Meets Multi-branch Models
https://github.com/huashen218/bidirectional-human-ai-alignment
공식 코드https://github.com/huawei-noah/vanillanet
공식 코드https://github.com/hugozhl/cafe
공식 코드CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models
https://github.com/ictmcg/newsint
공식 코드Exploring news intent and its application: A theory-driven approach
https://github.com/jiahaoljh/mapvectorizationevaltoolkit
공식 코드Online Map Vectorization for Autonomous Driving: A Rasterization Perspective
https://github.com/jiarui-liu/ip
공식 코드Implicit Personalization in Language Models: A Systematic Study
https://github.com/jlcmoore/valueaggregation
공식 코드https://github.com/josangyoung/official-poem
공식 코드POEM: Polarization of Embeddings for Domain-Invariant Representations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.