https://github.com/mingyue-cheng/instructtime
공식 코드Advancing Time Series Classification with Multimodal Language Modeling
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/mingyuj666/stockagent
공식 코드https://github.com/minhtannguyen/transformer-mgk
공식 코드https://github.com/minimalparts/nonce2vec
공식 코드High-risk learning: acquiring new word vectors from tiny data
https://github.com/mininglamp-mllm/hmllm
공식 코드https://github.com/mininglamp-technology/asr-blockformer
공식 코드Improving Mandarin Speech Recogntion with Block-augmented Transformer
https://github.com/minkaixu/fpo
공식 코드$f$-PO: Generalizing Preference Optimization with $f$-divergence Minimization
https://github.com/minkjung/blankcollapse
공식 코드Blank Collapse: Compressing CTC emission for the faster decoding
https://github.com/mirelleb/induced-rationales-markup-tokens
공식 코드https://github.com/mireshghallah/mixmatch
공식 코드Mix and Match: Learning-free Controllable Text Generation using Energy Language Models
https://github.com/mirthai/med3dvlm
공식 코드Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis
https://github.com/mirunabetianu/dallmi
공식 코드DALLMi: Domain Adaption for LLM-based Multi-label Classifier
https://github.com/mistralai/mistral-inference
공식 코드https://github.com/mistralai/mistral-src
공식 코드https://github.com/mistyreed63849/graph-llm
공식 코드GraphLLM: Boosting Graph Reasoning Ability of Large Language Model
https://github.com/mit-han-lab/lite-transformer
공식 코드https://github.com/mit-han-lab/llm-awq
공식 코드AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
https://github.com/mit-han-lab/neurips-micronet
공식 코드https://github.com/mit-han-lab/streaming-llm
공식 코드https://github.com/mit-ll/linkq
공식 코드LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering
https://github.com/mitjanikolaus/multimodal-predicate-noun-dependencies
공식 코드Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?
https://github.com/mitscha/strassennets
공식 코드https://github.com/miulab/implicitbot
공식 코드Zero-Shot Prompting for Implicit Intent Prediction and Recommendation with Commonsense Reasoning
https://github.com/miulab/lmrec-survey
공식 코드Augment or Not? A Comparative Study of Pure and Augmented Large Language Model Recommenders
https://github.com/miulab/taiwan-llama
공식 코드Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model
https://github.com/miulab/taiwan-llm
공식 코드Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model
https://github.com/mizuno-group/notationalinconsistency
공식 코드Impact of SMILES Notational Inconsistencies on Chemical Language Model Performance
https://github.com/mj-jang/beyond-distributional
공식 코드Beyond Distributional Hypothesis: Let Language Models Learn Meaning-Text Correspondence
https://github.com/mj-storytelling/DiversityTuning
공식 코드Modifying Large Language Model Post-Training for Diverse Creative Writing
https://github.com/mjs227/gfolds
공식 코드Exploring Graph Representations of Logical Forms for Language Modeling
https://github.com/mjy1111/bake
공식 코드Untying the Reversal Curse via Bidirectional Language Model Editing
https://github.com/mkandai/llms-in-the-loop
공식 코드https://github.com/mkc1000/kl-fixed-mixture
공식 코드https://github.com/mklimasz/transferable-modularity
공식 코드Is Modularity Transferable? A Case Study through the Lens of Knowledge Distillation
https://github.com/mkuchnik/relm
공식 코드https://github.com/ml-ailab/ophglm
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.