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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nomizy/think_net_prompt
공식 코드https://github.com/norahalshahrani/bert_synonym_attack
공식 코드Arabic Synonym BERT-based Adversarial Examples for Text Classification
https://github.com/norakassner/BERT-kNN
공식 코드BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA
https://github.com/norskregnesentral/conv_feedback
공식 코드Conversational Feedback in Scripted versus Spontaneous Dialogues: A Comparative Analysis
https://github.com/northsky0307/dppa-pruning-method-for-large-language-model-to-model-merging
공식 코드DPPA: Pruning Method for Large Language Model to Model Merging
https://github.com/nouran-khallaf/why-tough
공식 코드Reading Between the Lines: A dataset and a study on why some texts are tougher than others
https://github.com/nsothman/chartformer
공식 코드ChartFormer: A Large Vision Language Model for Converting Chart Images into Tactile Accessible SVGs
https://github.com/nttcslab-nlp/doc_lm
공식 코드https://github.com/ntunlp/kmlm
공식 코드Enhancing Multilingual Language Model with Massive Multilingual Knowledge Triples
https://github.com/ntunlp/opensource-llms-better-than-openai
공식 코드ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?
https://github.com/ntunlplab/fecs
공식 코드https://github.com/nu-dialogue/jmultiwoz
공식 코드JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset
https://github.com/nulog/nulog
공식 코드https://github.com/nuochenpku/Graph-Reasoning-LLM
공식 코드GraphWiz: An Instruction-Following Language Model for Graph Problems
https://github.com/nuochenpku/comedy
공식 코드https://github.com/nusioraprivacy/eaas-privacy
공식 코드Split-and-Denoise: Protect large language model inference with local differential privacy
https://github.com/nusnlp/mlconvgec2018
공식 코드A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction
https://github.com/nusnlp/reacts
공식 코드Just What You Desire: Constrained Timeline Summarization with Self-Reflection for Enhanced Relevance
https://github.com/nuster1128/llm_agent_memory_survey
공식 코드A Survey on the Memory Mechanism of Large Language Model based Agents
https://github.com/nuster1128/memengine
공식 코드MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents
https://github.com/nverma1/merging-ffs-compression
공식 코드https://github.com/nverma1/merging-text-transformers
공식 코드Merging Text Transformer Models from Different Initializations
https://github.com/nvidia/tensorrt-llm
공식 코드AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
https://github.com/nvlabs/coat
공식 코드COAT: Compressing Optimizer states and Activation for Memory-Efficient FP8 Training
https://github.com/nvlabs/fveval
공식 코드FVEval: Understanding Language Model Capabilities in Formal Verification of Digital Hardware
https://github.com/nvlabs/minitron
공식 코드Compact Language Models via Pruning and Knowledge Distillation
https://github.com/nvlabs/prismer
공식 코드https://github.com/nvshrao/social_gaze
공식 코드SocialGaze: Improving the Integration of Human Social Norms in Large Language Models
https://github.com/nx-ai/mlstm_kernels
공식 코드Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels
https://github.com/nx-ai/xlstm
공식 코드https://github.com/nxphi47/multiagent_crosstranslate
공식 코드Cross-model Back-translated Distillation for Unsupervised Machine Translation
https://github.com/nyonicai/nyonic-public
공식 코드https://github.com/nyu-dl/bert-gen
공식 코드BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model
https://github.com/nyu-dl/dl4marco-bert
공식 코드https://github.com/nyu-dl/gated_word_char_rlm
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.