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Language Modeling

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

https://github.com/getao/icae

공식 코드

In-context Autoencoder for Context Compression in a Large Language Model

https://github.com/ggchen1997/steps_bioinformatics

공식 코드

Structure-aware Protein Self-supervised Learning

https://github.com/ggcr/tinyemo

공식 코드

TinyEmo: Scaling down Emotional Reasoning via Metric Projection

https://github.com/ghrua/ngramres

공식 코드

$N$-gram Is Back: Residual Learning of Neural Text Generation with $n$-gram Language Model

https://github.com/ghrua/seqpe

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SeqPE: Transformer with Sequential Position Encoding

https://github.com/ghupppp/memorysharingllm

공식 코드

Memory Sharing for Large Language Model based Agents

https://github.com/gingasan/lemon

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Rethinking Masked Language Modeling for Chinese Spelling Correction

https://github.com/gingasan/mometas

공식 코드

Forging Multiple Training Objectives for Pre-trained Language Models via Meta-Learning

https://github.com/ginnm/proteinpretraining

공식 코드

PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications

https://github.com/giskard-ai/realharm

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RealHarm: A Collection of Real-World Language Model Application Failures

https://github.com/git-disl/awesome-llm-game-agent-papers

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A Survey on Large Language Model-Based Game Agents

https://github.com/git-disl/gptlens

공식 코드

Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives

https://github.com/git-disl/safety-tax

공식 코드

Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable

https://github.com/gitter-lab/Assay2Mol

공식 코드

Assay2Mol: large language model-based drug design using BioAssay context

https://github.com/gitter-lab/chemlml

공식 코드

Chemical Language Model Linker: blending text and molecules with modular adapters

https://github.com/gitycc/phonetic_mlm

공식 코드

Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition

https://github.com/giventicket/cycleformer

공식 코드

CycleFormer : TSP Solver Based on Language Modeling

https://github.com/gjwubyron/icu

공식 코드

ICU: Conquering Language Barriers in Vision-and-Language Modeling by Dividing the Tasks into Image Captioning and Language Understanding

https://github.com/gk0wk/xgraphrag

공식 코드

XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation

https://github.com/gkakogeorgiou/attmask

공식 코드

What to Hide from Your Students: Attention-Guided Masked Image Modeling

https://github.com/gkw0010/endochat

공식 코드

EndoChat: Grounded Multimodal Large Language Model for Endoscopic Surgery

https://github.com/glaciohound/lm-steer

공식 코드

Word Embeddings Are Steers for Language Models

https://github.com/glemhel/activationsgradientscompressionformp

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Activations and Gradients Compression for Model-Parallel Training

https://github.com/glnmario/cwr4lsc

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Analysing Lexical Semantic Change with Contextualised Word Representations

https://github.com/glowworm-cell/lict

공식 코드

Objectively Evaluating the Reliability of Cell Type Annotation Using LLM-Based Strategies

https://github.com/gls0425/linvt

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LinVT: Empower Your Image-level Large Language Model to Understand Videos

https://github.com/gmaher/llmpc

공식 코드

LLMPC: Large Language Model Predictive Control

https://github.com/gmftbygmftby/copyisallyouneed

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Copy Is All You Need

https://github.com/gmlwns2000/sea-attention

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SEA: Sparse Linear Attention with Estimated Attention Mask

https://github.com/gmpoli/electramed

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ELECTRAMed: a new pre-trained language representation model for biomedical NLP

https://github.com/gmum/rsoftmax

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r-softmax: Generalized Softmax with Controllable Sparsity Rate

https://github.com/gnimixy/lancer

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Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling

https://github.com/godofhoe/gene-language-correspondence

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General Mechanism of Evolution Shared by Proteins and Words

https://github.com/going-doer/judge_code_efficiency

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Rethinking Code Refinement: Learning to Judge Code Efficiency

https://github.com/gokamoda/TTA4FactualProbing

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Test-time Augmentation for Factual Probing

https://github.com/gokulkarthik/deformable-detr

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An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers

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