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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/sarahmart/hardmath
공식 코드HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics
https://github.com/sarthmit/BRIMs
공식 코드https://github.com/sashank06/CCNLG-emotion
공식 코드Emotional Neural Language Generation Grounded in Situational Contexts
https://github.com/sashayd/mat
공식 코드Jump to Conclusions: Short-Cutting Transformers With Linear Transformations
https://github.com/satoshi-kosugi/masked-style-modeling
공식 코드Personalized Image Enhancement Featuring Masked Style Modeling
https://github.com/satoshi-kosugi/pg-ia-nilut
공식 코드Prompt-Guided Image-Adaptive Neural Implicit Lookup Tables for Interpretable Image Enhancement
https://github.com/satpreetsingh/racer
공식 코드RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health Interviews
https://github.com/satya77/Transformer_Temporal_Tagger
공식 코드BERT got a Date: Introducing Transformers to Temporal Tagging
https://github.com/sauc-abadal/alt
공식 코드https://github.com/sautenich/uav-vla
공식 코드UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation
https://github.com/savannahxu79/linkprompt
공식 코드$\textit{LinkPrompt}$: Natural and Universal Adversarial Attacks on Prompt-based Language Models
https://github.com/sb-jang/timelychat
공식 코드From What to Respond to When to Respond: Timely Response Generation for Open-domain Dialogue Agents
https://github.com/sberdevices/golos
공식 코드https://github.com/sbu-dsl/prosody-analysis-of-audiobooks
공식 코드https://github.com/scalable-model-editing/unified-model-editing
공식 코드Is Bigger Edit Batch Size Always Better? -- An Empirical Study on Model Editing with Llama-3
https://github.com/scandukuri/assistant-gate
공식 코드STaR-GATE: Teaching Language Models to Ask Clarifying Questions
https://github.com/schowdhury671/meerkat
공식 코드Meerkat: Audio-Visual Large Language Model for Grounding in Space and Time
https://github.com/schwartz-lab-nlp/model_size_and_gender_bias
공식 코드Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias
https://github.com/sciencenlp-lab/llm-ssc
공식 코드Multi-label Sequential Sentence Classification via Large Language Model
https://github.com/scientific-computing-lab-nrcn/monocoder
공식 코드MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
https://github.com/scientific-computing-lab-nrcn/mpi-rical
공식 코드MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with Transformers
https://github.com/scientific-computing-lab/monocoder
공식 코드MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
https://github.com/scir-hi/moltailor
공식 코드MolTailor: Tailoring Chemical Molecular Representation to Specific Tasks via Text Prompts
https://github.com/scitix/MEAP
공식 코드Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More
https://github.com/scottviteri/markoviantraining
공식 코드https://github.com/sdadas/polish-sentence-evaluation
공식 코드Training Effective Neural Sentence Encoders from Automatically Mined Paraphrases
https://github.com/sdamirsa/llm-vlm-in-gastroenterology
공식 코드https://github.com/sdongchuanqi/third-party-supervised-aligner
공식 코드https://github.com/se7esx/eib
공식 코드https://github.com/seal-rg/recurrent-pretraining
공식 코드Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
https://github.com/sebastian-steindl/CoPrUS_data
공식 코드CoPrUS: Consistency Preserving Utterance Synthesis towards more realistic benchmark dialogues
https://github.com/sebschu/entity-tracking-lms
공식 코드https://github.com/sebulo/LoQT
공식 코드https://github.com/secureaiautonomylab/conditionalvlm
공식 코드https://github.com/selimfirat/bilkent-turkish-writings-dataset
공식 코드TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.