https://github.com/tanyuqian/redco
공식 코드RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs
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/taoshen58/lexmae
공식 코드LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval
https://github.com/taosong2019/utel
공식 코드Knowing Where and What: Unified Word Block Pretraining for Document Understanding
https://github.com/taowu974/leam
공식 코드LEAM: A Prompt-only Large Language Model-enabled Antenna Modeling Method
https://github.com/taoyang225/ad-drop
공식 코드AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning
https://github.com/tapilot-crossing/tapilot_code
공식 코드Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents
https://github.com/tat-nlp/SART
공식 코드https://github.com/tatsu-lab/alpaca_farm
공식 코드Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
https://github.com/tatsu-lab/mlm_inductive_bias
공식 코드On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies
https://github.com/taylorwwebb/emergent_analogies_llm
공식 코드https://github.com/tbs17/MathBERT
공식 코드MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education
https://github.com/tchewik/corefhd
공식 코드Light Coreference Resolution for Russian with Hierarchical Discourse Features
https://github.com/tdmeeste/SparseSeqModels
공식 코드https://github.com/tdooms/bilinear-decomposition
공식 코드Bilinear MLPs enable weight-based mechanistic interpretability
https://github.com/tdopierre/ProtAugment
공식 코드ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learning
https://github.com/tdross/dna-llm
공식 코드Chaining thoughts and LLMs to learn DNA structural biophysics
https://github.com/teapot123/fine-grained-entity-typing
공식 코드Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation
https://github.com/tech-srl/layer_norm_expressivity_role
공식 코드On the Expressivity Role of LayerNorm in Transformers' Attention
https://github.com/tech-srl/slm-code-generation
공식 코드https://github.com/tech-srl/weighted_lstar
공식 코드Learning Deterministic Weighted Automata with Queries and Counterexamples
https://github.com/technion-cs-nlp/bias-probing
공식 코드Debiasing Methods in Natural Language Understanding Make Bias More Accessible
https://github.com/technion-cs-nlp/hallucination-mitigation
공식 코드Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs
https://github.com/technion-cs-nlp/peap
공식 코드https://github.com/teelinsan/camoscio
공식 코드https://github.com/temporarylora/temp-lora
공식 코드With Greater Text Comes Greater Necessity: Inference-Time Training Helps Long Text Generation
https://github.com/temu-bsc/gpt3-queries
공식 코드On the Multilingual Capabilities of Very Large-Scale English Language Models
https://github.com/tencent-ailab/persona-hub
공식 코드https://github.com/tencent/hunyuandit
공식 코드https://github.com/tencentarc/flm
공식 코드Accelerating Vision-Language Pretraining with Free Language Modeling
https://github.com/tencentarc/seed-story
공식 코드SEED-Story: Multimodal Long Story Generation with Large Language Model
https://github.com/tenghuilee/scalingcapfusedvisionlm
공식 코드Scaling Capability in Token Space: An Analysis of Large Vision Language Model
https://github.com/tengxiao1/cal-dpo
공식 코드Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment
https://github.com/tengxiao1/gsil
공식 코드https://github.com/tensorflow/lingvo
공식 코드https://github.com/tensorflow/mesh
공식 코드https://github.com/tensorflow/models
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.