https://github.com/thu-ml/lm-calibration
공식 코드Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models
Papers with Code 아카이브
Language Modeling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/thu-nics/moa
공식 코드MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression
https://github.com/thuccslab/mergeguard
공식 코드https://github.com/thudm/autowebglm
공식 코드AutoWebGLM: A Large Language Model-based Web Navigating Agent
https://github.com/thudm/cogview2
공식 코드CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers
https://github.com/thudm/cogvlm
공식 코드https://github.com/thudm/glm-130b
공식 코드https://github.com/thudm/glm-4-voice
공식 코드GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot
https://github.com/thudm/mathglm
공식 코드https://github.com/thudm/p-tuning-v2
공식 코드P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
https://github.com/thudm/scholar-profiling
공식 코드https://github.com/thudm/self-contrast
공식 코드Extensive Self-Contrast Enables Feedback-Free Language Model Alignment
https://github.com/thudm/t1
공식 코드Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
https://github.com/thudm/webglm
공식 코드WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences
https://github.com/thudm/whoiswho
공식 코드https://github.com/thuhcsi/contextual-biasing-dataset
공식 코드CB-Conformer: Contextual biasing Conformer for biased word recognition
https://github.com/thunderous77/glape
공식 코드GLaPE: Gold Label-agnostic Prompt Evaluation and Optimization for Large Language Model
https://github.com/thunlp/ChartCoder
공식 코드ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation
https://github.com/thunlp/LegalPLMs
공식 코드Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents
https://github.com/thunlp/OpenKE
공식 코드https://github.com/thunlp/SDLM-pytorch
공식 코드https://github.com/thunlp/SelectiveMasking
공식 코드Train No Evil: Selective Masking for Task-Guided Pre-Training
https://github.com/thunlp/SememeRNN
공식 코드Improving Sequence Modeling Ability of Recurrent Neural Networks via Sememes
https://github.com/thunlp/apb
공식 코드https://github.com/thunlp/dpt
공식 코드Prompt Tuning for Discriminative Pre-trained Language Models
https://github.com/thunlp/knowledgeableprompttuning
공식 코드Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
https://github.com/thunlp/pevl
공식 코드PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models
https://github.com/thunlp/seq2seq-prompt
공식 코드Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models
https://github.com/thunlp/tritonbench
공식 코드TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators
https://github.com/tianduowang/diffaug
공식 코드Differentiable Data Augmentation for Contrastive Sentence Representation Learning
https://github.com/tiangeluo/regionfocus
공식 코드https://github.com/tianhaoshi2001/lsat
공식 코드Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems
https://github.com/tianjunz/hir
공식 코드The Wisdom of Hindsight Makes Language Models Better Instruction Followers
https://github.com/tiannuo-yang/searchagent-x
공식 코드Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents
https://github.com/tianyi-lab/superfiltering
공식 코드Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning
https://github.com/tianyu-z/vcr
공식 코드VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.