https://github.com/fuyu-quant/iblm
공식 코드Inductive-bias Learning: Generating Code Models with Large Language Model
Papers with Code 아카이브
Language Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fuzhiyi/taco
공식 코드Contextual Representation Learning beyond Masked Language Modeling
https://github.com/ga642381/SpeechPrompt
공식 코드https://github.com/ga642381/speech-trident
공식 코드Codec-SUPERB @ SLT 2024: A lightweight benchmark for neural audio codec models
https://github.com/gabeguo/any-order-speculative-decoding
공식 코드Reviving Any-Subset Autoregressive Models with Principled Parallel Sampling and Speculative Decoding
https://github.com/gabriellasky/claim_optimization
공식 코드https://github.com/gair-nlp/octothinker
공식 코드OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling
https://github.com/galirage/spreadsheet-intelligence
공식 코드https://github.com/galirage/xmldriven-diagram-understanding
공식 코드https://github.com/ganchengguang/resume-IE-via-prompt
공식 코드A Few-shot Approach to Resume Information Extraction via Prompts
https://github.com/gangiswag/llm-reranker
공식 코드FIRST: Faster Improved Listwise Reranking with Single Token Decoding
https://github.com/gaopengcuhk/ballad
공식 코드A Simple Long-Tailed Recognition Baseline via Vision-Language Model
https://github.com/gaopengcuhk/tip-adapter
공식 코드Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
https://github.com/gasolsun36/dynamicrag
공식 코드https://github.com/gasolsun36/tog
공식 코드Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
https://github.com/gatech-eic/edge-llm
공식 코드https://github.com/gatech-eic/longmamba
공식 코드LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field Enlargement
https://github.com/gatenlp/h3prompt
공식 코드https://github.com/gatiaher/using-large-language-models-to-replicate-human-subject-studies
공식 코드Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies
https://github.com/gautamshahi/fakeclaim
공식 코드https://github.com/gavin001201/cof
공식 코드CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models
https://github.com/gblackout/lm-os
공식 코드https://github.com/gc-js/creopep
공식 코드CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and Optimization
https://github.com/gchochla/demux-memo
공식 코드Leveraging Label Correlations in a Multi-label Setting: A Case Study in Emotion
https://github.com/gcyzsl/o3-llm-unlearning
공식 코드https://github.com/geekjuruo/probexpan
공식 코드Contrastive Learning with Hard Negative Entities for Entity Set Expansion
https://github.com/gen-verse/reasonflux
공식 코드ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates
https://github.com/gen-verse/scoreflow
공식 코드ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization
https://github.com/generative-social-choice/chatbot_personalization_data
공식 코드https://github.com/genezc/minidisc
공식 코드MiniDisc: Minimal Distillation Schedule for Language Model Compression
https://github.com/genggengcss/pdkgc
공식 코드Prompting Disentangled Embeddings for Knowledge Graph Completion with Pre-trained Language Model
https://github.com/geobrain-ai/geogalactica
공식 코드GeoGalactica: A Scientific Large Language Model in Geoscience
https://github.com/geondopark/ckd
공식 코드Distilling Linguistic Context for Language Model Compression
https://github.com/georgedrayson/model_collapse
공식 코드Machine-generated text detection prevents language model collapse
https://github.com/gerulata/slovakbert
공식 코드https://github.com/getalp/Flaubert
공식 코드FlauBERT: Unsupervised Language Model Pre-training for French
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.