https://github.com/rwth-i6/returnn
공식 코드Librispeech Transducer Model with Internal Language Model Prior Correction
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/rwth-i6/returnn-experiments/tree/master/2021-transducer
공식 코드Librispeech Transducer Model with Internal Language Model Prior Correction
https://github.com/ryang1119/ATOSS
공식 코드https://github.com/rycolab/earleys-algo
공식 코드https://github.com/rycolab/naturalistic-causal-probing
공식 코드https://github.com/rycolab/parsing-as-tagging
공식 코드https://github.com/rycolab/spanningtrees
공식 코드https://github.com/ryokamoi/wice
공식 코드https://github.com/ryuliuxiaodong/DefSent-Plus
공식 코드https://github.com/s-gupta/visual-concepts
공식 코드https://github.com/s-mizuki-nlp/semantic_specialization_for_wsd
공식 코드Semantic Specialization for Knowledge-based Word Sense Disambiguation
https://github.com/sa5r/mrca
공식 코드Multiple Relations Classification using Imbalanced Predictions Adaptation
https://github.com/saba96/img-cap-metrics-robustness
공식 코드An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics
https://github.com/sabyasachi-kamila/ax-mabsa
공식 코드AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis
https://github.com/safakkbilici/conditional-variational-transformer
공식 코드Transformers as Neural Augmentors: Class Conditional Sentence Generation via Variational Bayes
https://github.com/sahithyaravi/comet-m
공식 코드COMET-M: Reasoning about Multiple Events in Complex Sentences
https://github.com/sahithyaravi1493/coref_csk
공식 코드What happens before and after: Multi-Event Commonsense in Event Coreference Resolution
https://github.com/sahoonihar/indibias
공식 코드IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context
https://github.com/saikeshav/mfl
공식 코드https://github.com/sail-sg/closer-look-llm-unlearning
공식 코드A Closer Look at Machine Unlearning for Large Language Models
https://github.com/sailordiary/deep-face-vsr
공식 코드Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech Recognition
https://github.com/sajastu/reddit_collector
공식 코드TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts
https://github.com/salesforce/DocNLI
공식 코드DocNLI: A Large-scale Dataset for Document-level Natural Language Inference
https://github.com/salesforce/compedit
공식 코드Improving Factual Consistency in Summarization with Compression-Based Post-Editing
https://github.com/salesforce/mpt
공식 코드https://github.com/salesforce/simplification
공식 코드SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages
https://github.com/sallmanm/synsim
공식 코드https://github.com/sameenmaruf/selective-attn
공식 코드Selective Attention for Context-aware Neural Machine Translation
https://github.com/samuael/postprocessed_geez_asr
공식 코드https://github.com/samuelstevens/bert-edits
공식 코드An Investigation of Language Model Interpretability via Sentence Editing
https://github.com/samuelstevens/sentence-editing-interpretability
공식 코드An Investigation of Language Model Interpretability via Sentence Editing
https://github.com/sandropezzelle/fill-in-the-quant
공식 코드Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers
https://github.com/sangjoon-park/medical_x-vl
공식 코드https://github.com/sangminwoo/explore-and-match
공식 코드https://github.com/sap-samples/acl2023-micse
공식 코드miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings
https://github.com/sapienzanlp/leakdistill
공식 코드Incorporating Graph Information in Transformer-based AMR Parsing
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.