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Language Modeling
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ryanliut/llm_lexsem
공식 코드https://github.com/rycolab/causalgeom
공식 코드https://github.com/rycolab/context-reading-time
공식 코드https://github.com/rycolab/flare
공식 코드https://github.com/rycolab/neural-network-recognizers
공식 코드https://github.com/rycolab/parsing-as-tagging
공식 코드https://github.com/rycolab/probing-via-prompting
공식 코드https://github.com/rycolab/psycho-toke
공식 코드On the Proper Treatment of Tokenization in Psycholinguistics
https://github.com/rycolab/stack-transformer
공식 코드https://github.com/ryeoat3/gomin
공식 코드https://github.com/rymarinelli/leaking_lora
공식 코드Leaking LoRa: An Evaluation of Password Leaks and Knowledge Storage in Large Language Models
https://github.com/ryoungj/obsscaling
공식 코드Observational Scaling Laws and the Predictability of Language Model Performance
https://github.com/ryutaro-a/sumrec
공식 코드SumRec: A Framework for Recommendation using Open-Domain Dialogue
https://github.com/s-gupta/visual-concepts
공식 코드https://github.com/s-nlp/s3
공식 코드S3: A Simple Strong Sample-effective Multimodal Dialog System
https://github.com/s-t-full-text-knowledge-mining/ssci-bert
공식 코드SsciBERT: A Pre-trained Language Model for Social Science Texts
https://github.com/s-vigneshwaran/revisiting-the-classics
공식 코드https://github.com/s222416822/llmqfl
공식 코드LLM-QFL: Distilling Large Language Model for Quantum Federated Learning
https://github.com/sEhsanTaher/Beheshti-NER
공식 코드https://github.com/sa5r/kgrp
공식 코드Knowledge Graph Completion using Structural and Textual Embeddings
https://github.com/sabyasachi-kamila/ax-mabsa
공식 코드AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis
https://github.com/sacmehta/EdgeNets
공식 코드ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
https://github.com/sacmehta/PRU
공식 코드https://github.com/sacmehta/delight
공식 코드https://github.com/safeailab/eagle
공식 코드EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
https://github.com/saffronh/ccai
공식 코드Collective Constitutional AI: Aligning a Language Model with Public Input
https://github.com/safolab-wisc/fiubench
공식 코드Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
https://github.com/sai990323/tallrec
공식 코드https://github.com/saic-fi/bayesian-prompt-learning
공식 코드Bayesian Prompt Learning for Image-Language Model Generalization
https://github.com/saifkhichi96/situational-llm
공식 코드SituationalLLM: Proactive language models with scene awareness for dynamic, contextual task guidance
https://github.com/sail-sg/regmix
공식 코드RegMix: Data Mixture as Regression for Language Model Pre-training
https://github.com/sail-sg/sailor-llm
공식 코드https://github.com/sail-sg/sdft
공식 코드Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
https://github.com/saitejautpala/dp_prompt
공식 코드Locally Differentially Private Document Generation Using Zero Shot Prompting
https://github.com/sajaddarabi/TAPER
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.