https://github.com/huangshulin123/blessing-generation
공식 코드Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation
Papers with Code 아카이브
Diversity
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/huawei-noah/CV-Backbones/tree/master/augvit_pytorch
공식 코드https://github.com/huawei-noah/SMARTS
공식 코드https://github.com/huawei-noah/noah-research/tree/master/conv_graph
공식 코드https://github.com/huawei-noah/vega
공식 코드https://github.com/huey0528/icml24didi
공식 코드DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation
https://github.com/huggingface/diffusers
공식 코드Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
https://github.com/hughnew/gapdiff
공식 코드Bridging the Gap between Learning and Inference for Diffusion-Based Molecule Generation
https://github.com/huihanlhh/culture-gen
공식 코드https://github.com/huijelee/ELF-HumanPreference
공식 코드https://github.com/hukenovs/easyportrait
공식 코드EasyPortrait -- Face Parsing and Portrait Segmentation Dataset
https://github.com/hukkelas/deep_privacy2
공식 코드https://github.com/hukkelas/full_body_anonymization
공식 코드https://github.com/human-analysis/diverse3dface
공식 코드Generating Diverse 3D Reconstructions from a Single Occluded Face Image
https://github.com/humancompatibleai/reducing-exploitability
공식 코드https://github.com/humphreymunn/modularityneat
공식 코드https://github.com/humuyan/korch
공식 코드https://github.com/hunan-tiger/reactdiff
공식 코드https://github.com/hunterj-lin/activeteacher
공식 코드https://github.com/hunyuanfeng/ccet2021
공식 코드A Chit-Chats Enhanced Task-Oriented Dialogue Corpora for Fuse-Motive Conversation Systems
https://github.com/huochf/WildHOI
공식 코드https://github.com/hussonnoismaxence/cdp
공식 코드Controlled Diversity with Preference : Towards Learning a Diverse Set of Desired Skills
https://github.com/hust-linyi/LENAS
공식 코드LENAS: Learning-based Neural Architecture Search and Ensemble for 3D Radiotherapy Dose Prediction
https://github.com/hustvl/groundingsuite
공식 코드GroundingSuite: Measuring Complex Multi-Granular Pixel Grounding
https://github.com/hwanheelee1993/UMIC
공식 코드UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learning
https://github.com/hxixixh/adaflow
공식 코드AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies
https://github.com/hxwork/handbooster_pytorch
공식 코드https://github.com/hxyfighter/molrl-mgpt
공식 코드De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
https://github.com/hyf1530588058/HeteroMorpheus
공식 코드HeteroMorpheus: Universal Control Based on Morphological Heterogeneity Modeling
https://github.com/hyperconnect/sem-ent
공식 코드Measuring and Improving Semantic Diversity of Dialogue Generation
https://github.com/hys-451/dexdeepfm
공식 코드DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine Model
https://github.com/hzlsaber/IPMix
공식 코드IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers
https://github.com/hzq950419/math-llava
공식 코드Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models
https://github.com/hzxie/awesome-3d-scene-generation
공식 코드https://github.com/i2-multimedia-lab/cdformer
공식 코드CDFormer:When Degradation Prediction Embraces Diffusion Model for Blind Image Super-Resolution
https://github.com/iPaw-AI-LAB/LawDNet_2024
공식 코드LawDNet: Enhanced Audio-Driven Lip Synthesis via Local Affine Warping Deformation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.