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Zero-shot Generalization

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/hojjat-mokhtarabadi/promptsource

Multitask Prompted Training Enables Zero-Shot Task Generalization

https://github.com/huage001/linfusion

CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

https://github.com/husheng12345/Unofficial-NeRF-Supervised-Deep-Stereo

NeRF-Supervised Deep Stereo

https://github.com/i-machine-think/machine-tasks

Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks

https://github.com/indu1ge/DepthMaster

Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation

https://github.com/intel-isl/MiDaS

ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

https://github.com/intuitive-robots/MoDE_Diffusion_Policy

Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning

https://github.com/isl-org/MiDaS

ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

https://github.com/jhu-medimage-reg/lumir_l2r

Beyond the LUMIR challenge: The pathway to foundational registration models

https://github.com/jia-hao999/samba

VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning

https://github.com/kehanlu/DeSTA2

DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment

https://github.com/lastmile-ai/aiconfig

From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models

https://github.com/lefteris12/multitask-schema-guided-dst

A Multi-Task BERT Model for Schema-Guided Dialogue State Tracking

https://github.com/longkangli/pfss-il

Learning the Travelling Salesperson Problem Requires Rethinking Generalization

https://github.com/lucidrains/gated-state-spaces-pytorch

Long Range Language Modeling via Gated State Spaces

https://github.com/lucidrains/scattering-compositional-learner

The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning

https://github.com/makora9143/pytorch-convcnp

Convolutional Conditional Neural Processes

https://github.com/masterxiong/modumorph

MetaMorph: Learning Universal Controllers with Transformers

https://github.com/maxwells-daemons/compositional-learning-experiments

Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks

https://github.com/meize0729/ccexpert

RSBuilding: Towards General Remote Sensing Image Building Extraction and Change Detection with Foundation Model

https://github.com/microsoft/mttl

Learning to Route Among Specialized Experts for Zero-Shot Generalization

https://github.com/mikomel/scattering-compositional-learner

The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning

https://github.com/mzhao98/DeepQLearning_CrossyRoad

Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics

https://github.com/nickgkan/3d_diffuser_actor

3D Diffuser Actor: Policy Diffusion with 3D Scene Representations

https://github.com/ondrejba/action_attention_iclr_22

Factored World Models for Zero-Shot Generalization in Robotic Manipulation

https://github.com/openbiolink/promptsource

Multitask Prompted Training Enables Zero-Shot Task Generalization

https://github.com/openlamm/lamm

Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE

https://github.com/patrickhaoy/ptp

What Can I Do Here? Learning New Skills by Imagining Visual Affordances

https://github.com/peterholderrieth/steerable_cnps

Convolutional Conditional Neural Processes

https://github.com/phigley/taxi

Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics

https://github.com/pwc-1/Paper-9/tree/main/5/vision_text_dual_encoder

Improving Diffusion Models for Scene Text Editing with Dual Encoders

https://github.com/r-pad/zephyr

ZePHyR: Zero-shot Pose Hypothesis Rating

https://github.com/richardrl/rlkit-relational

Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning

https://github.com/ruc-nlpir/flashrag

Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In

https://github.com/ryanjulian/embed2learn

Simulator Predictive Control: Using Learned Task Representations and MPC for Zero-Shot Generalization and Sequencing

https://github.com/s-nlp/sgdd-tst

Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.