https://github.com/behavioral-data/blade
공식 코드BLADE: Benchmarking Language Model Agents for Data-Driven Science
Papers with Code 아카이브
Language Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/behavioral-data/cognitive-reframing-of-negative-thoughts
공식 코드Cognitive Reframing of Negative Thoughts through Human-Language Model Interaction
https://github.com/belindal/erase
공식 코드https://github.com/belindal/taskbench500
공식 코드Quantifying Adaptability in Pre-trained Language Models with 500 Tasks
https://github.com/belisards/gunviolence_ptbr
공식 코드Into the crossfire: evaluating the use of a language model to crowdsource gun violence reports
https://github.com/ben-aaron188/who_is_gpt3
공식 코드Who is GPT-3? An Exploration of Personality, Values and Demographics
https://github.com/benjamin-mlr/first-align-then-predict
공식 코드First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
https://github.com/benzakenelad/BitFit
공식 코드BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models
https://github.com/berlino/gated_linear_attention
공식 코드Gated Linear Attention Transformers with Hardware-Efficient Training
https://github.com/berlino/seq_icl
공식 코드https://github.com/bethelmelesse/unifiedcrawl
공식 코드UnifiedCrawl: Aggregated Common Crawl for Affordable Adaptation of LLMs on Low-Resource Languages
https://github.com/better-chao/perceptual_abilities_evaluation
공식 코드Vision-Language Model for Object Detection and Segmentation: A Review and Evaluation
https://github.com/betterzh/sevlm-code
공식 코드Training A Small Emotional Vision Language Model for Visual Art Comprehension
https://github.com/betterzh/sevlm-for-visual-art-comprehension
공식 코드Training A Small Emotional Vision Language Model for Visual Art Comprehension
https://github.com/beyondguo/genius
공식 코드https://github.com/bfarzin/haha_2019_final
공식 코드Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction
https://github.com/bflameswift/uni-mumer
공식 코드https://github.com/bhattg/Decay-RNN-ACL-SRW2020
공식 코드How much complexity does an RNN architecture need to learn syntax-sensitive dependencies?
https://github.com/bhui97/pleak
공식 코드PLeak: Prompt Leaking Attacks against Large Language Model Applications
https://github.com/bias-barometer/birth-of-bias
공식 코드The Birth of Bias: A case study on the evolution of gender bias in an English language model
https://github.com/bigai-nlco/docgnre
공식 코드https://github.com/bigheiniu/grenade
공식 코드https://github.com/bigscience-workshop/Megatron-DeepSpeed
공식 코드What Language Model to Train if You Have One Million GPU Hours?
https://github.com/bigscience-workshop/architecture-objective
공식 코드What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?
https://github.com/bigscience-workshop/biomedical
공식 코드BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing
https://github.com/bigscience-workshop/carbon-footprint
공식 코드Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model
https://github.com/bilaliman/rv_explainability
공식 코드Generating Zero-shot Abstractive Explanations for Rumour Verification
https://github.com/bilel-bj/rosgpt_vision
공식 코드ROSGPT_Vision: Commanding Robots Using Only Language Models' Prompts
https://github.com/billhhh/krpo_llms_rl
공식 코드Kalman Filter Enhanced GRPO for Reinforcement Learning-Based Language Model Reasoning
https://github.com/billpsomas/rscir
공식 코드https://github.com/billptw/fasttrees
공식 코드FastTrees: Parallel Latent Tree-Induction for Faster Sequence Encoding
https://github.com/bin123apple/autocoder
공식 코드AutoCoder: Enhancing Code Large Language Model with \textsc{AIEV-Instruct}
https://github.com/bingreeky/MaAS
공식 코드https://github.com/biomedsciai/biomed-multi-omic
공식 코드BMFM-RNA: An Open Framework for Building and Evaluating Transcriptomic Foundation Models
https://github.com/birco-benchmark/birco
공식 코드BIRCO: A Benchmark of Information Retrieval Tasks with Complex Objectives
https://github.com/bitbol-lab/diffpalm
공식 코드Pairing interacting protein sequences using masked language modeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.