https://github.com/sun-hailong/aaai25-mos
공식 코드MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
Papers with Code 아카이브
Retrieval
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- 보존된 평가 기록
- 19
A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sun-hailong/lamda-pilot
공식 코드MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
https://github.com/sun-xl/ISC2021
공식 코드3rd Place: A Global and Local Dual Retrieval Solution to Facebook AI Image Similarity Challenge
https://github.com/sunanhe/meddr
공식 코드GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration
https://github.com/suncerock/EAsT-music-classification
공식 코드https://github.com/sungonce/cvnet
공식 코드https://github.com/sunju/pr_plain
공식 코드https://github.com/sunlab-osu/covid-faq
공식 코드COUGH: A Challenge Dataset and Models for COVID-19 FAQ Retrieval
https://github.com/sunnweiwei/mair
공식 코드MAIR: A Massive Benchmark for Evaluating Instructed Retrieval
https://github.com/sunnweiwei/rankgpt
공식 코드Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents
https://github.com/sunnynexus/retrollm
공식 코드RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation
https://github.com/sunnynexus/search-o1
공식 코드https://github.com/suntongtongtong/benchmark-robustness-text-image-compose-retrieval
공식 코드https://github.com/sunxiaojie99/attempt
공식 코드Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval
https://github.com/sunxiaojie99/mural
공식 코드A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval
https://github.com/sunxiaojie99/reproducibility-for-madral
공식 코드Reproducibility Analysis and Enhancements for Multi-Aspect Dense Retriever with Aspect Learning
https://github.com/suoych/keds
공식 코드Knowledge-Enhanced Dual-stream Zero-shot Composed Image Retrieval
https://github.com/supercomputing-system-ai-lab/megafold
공식 코드MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction Models
https://github.com/superctj/pylon
공식 코드https://github.com/sureli/dicyr_code
공식 코드https://github.com/surisdi/youtube-8m
공식 코드https://github.com/surrey-nlp/PLOD-AbbreviationDetection
공식 코드PLOD: An Abbreviation Detection Dataset for Scientific Documents
https://github.com/susavlsh10/espn-v1
공식 코드https://github.com/sustcsonglin/flash-linear-attention
공식 코드Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling
https://github.com/suu990901/Dial-MAE
공식 코드Dial-MAE: ConTextual Masked Auto-Encoder for Retrieval-based Dialogue Systems
https://github.com/suziai/gui-tools
공식 코드Proceedings of the 5th International Workshop on Reading Music Systems
https://github.com/svakulenk0/ODExploration_data
공식 코드https://github.com/svakulenk0/cast_evaluation
공식 코드A Comparison of Question Rewriting Methods for Conversational Passage Retrieval
https://github.com/svthapa/more
공식 코드MoRE: Multi-Modal Contrastive Pre-training with Transformers on X-Rays, ECGs, and Diagnostic Report
https://github.com/swagatikadash010/gender_age
공식 코드Fairness in Image Search: A Study of Occupational Stereotyping in Image Retrieval and its Debiasing
https://github.com/swati17293/kg-multi-bias
공식 코드https://github.com/sweetpeach/ReCode
공식 코드https://github.com/swetha5/multi_sinkhorn_knopp
공식 코드https://github.com/swing-research/numerical_interferometry
공식 코드Fast Optical System Identification by Numerical Interferometry
https://github.com/swing-research/opu_phase
공식 코드Don't take it lightly: Phasing optical random projections with unknown operators
https://github.com/swing-research/tls_phase
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.