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Text Infilling

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Text Infilling is the task of predicting missing spans of text which are consistent with the preceding and subsequent text. Text Infilling is a generalization of the cloze task—cloze historically refers to infilling individual words.

Source: Enabling Language Models to Fill in the Blanks

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/VegB/Text_Infilling

공식 코드

https://github.com/acmi-lab/mvp

공식 코드

Model-tuning Via Prompts Makes NLP Models Adversarially Robust

https://github.com/atulkum/pointer_summarizer

공식 코드

Nutribullets Hybrid: Multi-document Health Summarization

https://github.com/chrisdonahue/ilm

공식 코드

Enabling Language Models to Fill in the Blanks

https://github.com/darsh10/Nutribullets

공식 코드

Nutribullets Hybrid: Multi-document Health Summarization

https://github.com/dayihengliu/Text-Infilling-Gradient-Search

공식 코드

TIGS: An Inference Algorithm for Text Infilling with Gradient Search

https://github.com/facebookresearch/electra-fewshot-learning

공식 코드

Prompting ELECTRA: Few-Shot Learning with Discriminative Pre-Trained Models

https://github.com/hanjiale/genpt

공식 코드

Generative Prompt Tuning for Relation Classification

https://github.com/ibm/reprogbert

공식 코드

Reprogramming Pretrained Language Models for Antibody Sequence Infilling

https://github.com/jackferrellncsu/drums-nlp-codesnapshot

공식 코드

Conformal prediction for text infilling and part-of-speech prediction

https://github.com/jacklishufan/lavida

공식 코드

LaViDa: A Large Diffusion Language Model for Multimodal Understanding

https://github.com/kakaobrain/magvlt

공식 코드

MAGVLT: Masked Generative Vision-and-Language Transformer

https://github.com/ktxlh/TrajGPT

공식 코드

TrajGPT: Controlled Synthetic Trajectory Generation Using a Multitask Transformer-Based Spatiotemporal Model

https://github.com/michaelzhouwang/sequence_span_rewriting

공식 코드

Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting

https://github.com/nlpcode/mcmcxlnet

공식 코드

Show Me How To Revise: Improving Lexically Constrained Sentence Generation with XLNet

https://github.com/qkaren/unsup_gen_for_cms_reasoning

공식 코드

Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning

https://github.com/rcalef/hcb_infilling

공식 코드

Towards Probabilistically-Sound Beam Search with Masked Language Models

https://github.com/rosewang2008/language_modeling_via_stochastic_processes

공식 코드

Language modeling via stochastic processes

https://github.com/sensellm/fim-se

공식 코드

Empowering Character-level Text Infilling by Eliminating Sub-Tokens

https://github.com/styfeng/SMERTI

공식 코드

Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text Exchange

https://github.com/tareknaous/camel

공식 코드

Having Beer after Prayer? Measuring Cultural Bias in Large Language Models

https://github.com/thu-coai/LOT-LongLM

공식 코드

LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation

https://github.com/thu-coai/ctrleval

공식 코드

CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation

https://github.com/thu-coai/lot-benchmark

공식 코드

LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation

https://github.com/zequnl/metafill

공식 코드

MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks

https://github.com/zichenwen1/dija

공식 코드

The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMs

https://worksheets.codalab.org/worksheets/0x9987b5d9cce74cf4b2a5f84b54ee447b

공식 코드

Enabling Language Models to Fill in the Blanks

https://github.com/reichang182/variable-length-piano-infilling

Enabling Language Models to Fill in the Blanks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.