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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/engineeringsoftware/coditt5
공식 코드CoditT5: Pretraining for Source Code and Natural Language Editing
https://github.com/engineeringsoftware/exlong
공식 코드A Tool for Generating Exceptional Behavior Tests With Large Language Models
https://github.com/ensec-ai/vlm-uncertainty-bench
공식 코드https://github.com/eoinkenny/regulatable_llms
공식 코드Regulation of Language Models With Interpretability Will Likely Result In A Performance Trade-Off
https://github.com/epfl-dlab/celmoc
공식 코드Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling
https://github.com/epfl-dlab/edisum
공식 코드https://github.com/epfl-dlab/forc
공식 코드Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling
https://github.com/epfl-dlab/invariant-language-models
공식 코드https://github.com/epfl-dlab/lamen
공식 코드https://github.com/epfl-dlab/llm-grounding-analysis
공식 코드A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia
https://github.com/epfl-dlab/sketchgcd
공식 코드Sketch-Guided Constrained Decoding for Boosting Blackbox Large Language Models without Logit Access
https://github.com/epfl-dlab/understanding-decoding
공식 코드https://github.com/epfl-ml4ed/ClickSightLBR25
공식 코드ClickSight: Interpreting Student Clickstreams to Reveal Insights on Learning Strategies via LLMs
https://github.com/epfllm/megatron-llm
공식 코드Tower: An Open Multilingual Large Language Model for Translation-Related Tasks
https://github.com/epflneuroailab/topolm
공식 코드TopoLM: brain-like spatio-functional organization in a topographic language model
https://github.com/epfml/comigs
공식 코드On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists
https://github.com/epfml/dynamic-sparse-flash-attention
공식 코드Faster Causal Attention Over Large Sequences Through Sparse Flash Attention
https://github.com/epoch-research/data-stock
공식 코드Will we run out of data? Limits of LLM scaling based on human-generated data
https://github.com/epoch-research/lm-algorithmic-progress
공식 코드https://github.com/eques-inc/pharma-llm-eval
공식 코드A Japanese Language Model and Three New Evaluation Benchmarks for Pharmaceutical NLP
https://github.com/ereboas/magicodec
공식 코드MagiCodec: Simple Masked Gaussian-Injected Codec for High-Fidelity Reconstruction and Generation
https://github.com/eric11eca/NeuralLog
공식 코드NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning
https://github.com/eric11eca/disco
공식 코드DISCO: Distilling Counterfactuals with Large Language Models
https://github.com/eric11eca/inference-information-probing
공식 코드Probing Linguistic Information For Logical Inference In Pre-trained Language Models
https://github.com/erichson/LipschitzRNN
공식 코드https://github.com/ericlee878/ScienceDeJargonizer
공식 코드De-jargonizing Science for Journalists with GPT-4: A Pilot Study
https://github.com/ernie-research/pixelgpt
공식 코드https://github.com/ernlavr/multihal
공식 코드MultiHal: Multilingual Dataset for Knowledge-Graph Grounded Evaluation of LLM Hallucinations
https://github.com/erogol/blagpt
공식 코드https://github.com/erxinyu/disbert
공식 코드Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables
https://github.com/espnet/espnet
공식 코드SpeechLMScore: Evaluating speech generation using speech language model
https://github.com/esyoon7/litta
공식 코드LI-TTA: Language Informed Test-Time Adaptation for Automatic Speech Recognition
https://github.com/esyoon7/rlhf-tlcr
공식 코드TLCR: Token-Level Continuous Reward for Fine-grained Reinforcement Learning from Human Feedback
https://github.com/eteced/arithmetic_finetuning_v1
공식 코드ArthModel: Enhance Arithmetic Skills to Large Language Model
https://github.com/eternaldolphin/lami-detr
공식 코드LaMI-DETR: Open-Vocabulary Detection with Language Model Instruction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.