https://github.com/polyagent/from-bytes-to-borsch
공식 코드From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation
Papers with Code 아카이브
Language Modeling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pooyafayyaz/fingerspelling-posenet
공식 코드Fingerspelling PoseNet: Enhancing Fingerspelling Translation with Pose-Based Transformer Models
https://github.com/popcornell/ASRLightningFT
공식 코드Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech Recognition
https://github.com/portal-cornell/robotouille
공식 코드Robotouille: An Asynchronous Planning Benchmark for LLM Agents
https://github.com/poruna-byte/gumbelsoft
공식 코드GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick
https://github.com/posttraining/post_training
공식 코드Human in the Loop Adaptive Optimization for Improved Time Series Forecasting
https://github.com/potamides/automatikz
공식 코드AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ
https://github.com/potamides/detikzify
공식 코드DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ
https://github.com/potamides/uniformers
공식 코드ByGPT5: End-to-End Style-conditioned Poetry Generation with Token-free Language Models
https://github.com/potosnakw/neuralforecast
공식 코드Investigating Compositional Reasoning in Time Series Foundation Models
https://github.com/ppartha03/Dialogue-Probe-Tasks-Public
공식 코드https://github.com/ppartha03/Semantic-Loss-Dialogue-Generation
공식 코드A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
https://github.com/pprp/acbench
공식 코드Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression
https://github.com/pprp/pruner-zero
공식 코드Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models
https://github.com/ppsmk388/GED
공식 코드Language Model Preference Evaluation with Multiple Weak Evaluators
https://github.com/prakash-aryan/qwen-arabic-project
공식 코드Resource-Aware Arabic LLM Creation: Model Adaptation, Integration, and Multi-Domain Testing
https://github.com/prash29/lager
공식 코드https://github.com/prashantkodali/precogiiith-hinglisheval-inlg-2022
공식 코드https://github.com/predlico/aragog
공식 코드https://github.com/prescient-design/lobster
공식 코드https://github.com/primerai/primer-research
공식 코드https://github.com/princeton-nlp/autocompressors
공식 코드https://github.com/princeton-nlp/calm-textgame
공식 코드Keep CALM and Explore: Language Models for Action Generation in Text-based Games
https://github.com/princeton-nlp/cepe
공식 코드Long-Context Language Modeling with Parallel Context Encoding
https://github.com/princeton-nlp/dinkytrain
공식 코드https://github.com/princeton-nlp/llm-shearing
공식 코드Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
https://github.com/princeton-nlp/lm-kernel-ft
공식 코드https://github.com/princeton-nlp/swe-agent
공식 코드EnIGMA: Enhanced Interactive Generative Model Agent for CTF Challenges
https://github.com/princeton-nlp/trime
공식 코드https://github.com/princeton-pli/meco
공식 코드Metadata Conditioning Accelerates Language Model Pre-training
https://github.com/princeton-pli/what-makes-good-rm
공식 코드What Makes a Reward Model a Good Teacher? An Optimization Perspective
https://github.com/pro-genai/lml-dap
공식 코드LML-DAP: Language Model Learning a Dataset for Data-Augmented Prediction
https://github.com/probcomp/hfppl
공식 코드Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs
https://github.com/probcomp/llamppl
공식 코드Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs
https://github.com/programmablebio/pepmlm
공식 코드https://github.com/project-baize/baize
공식 코드Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.