https://github.com/taoshuchang/conqord
공식 코드When to Trust LLMs: Aligning Confidence with Response Quality
Papers with Code 아카이브
Text Generation
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Text Generation is the task of generating text with the goal of appearing indistinguishable to human-written text. This task is more formally known as "natural language generation" in the literature.
Text generation can be addressed with Markov processes or deep generative models like LSTMs. Recently, some of the most advanced methods for text generation include BART, GPT and other GAN-based approaches. Text generation systems are evaluated either through human ratings or automatic evaluation metrics like METEOR, ROUGE, and BLEU.
Further readings:
<span style="color:grey; opacity: 0.6">( Image credit: Adversarial Ranking for Language Generation )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/taozhen1110/cat-llm
공식 코드https://github.com/taozhen1110/cudrt
공식 코드Towards Reliable Detection of LLM-Generated Texts: A Comprehensive Evaluation Framework with CUDRT
https://github.com/tararadvand74/llm-text-detection
공식 코드https://github.com/tareknaous/camel
공식 코드Having Beer after Prayer? Measuring Cultural Bias in Large Language Models
https://github.com/teigenzhang/escot
공식 코드ESCoT: Towards Interpretable Emotional Support Dialogue Systems
https://github.com/telepathylabsai/OpenDF
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/tencentarc/seed-story
공식 코드SEED-Story: Multimodal Long Story Generation with Large Language Model
https://github.com/tenghaohuang/affgen
공식 코드https://github.com/tensorflow/tensor2tensor
공식 코드https://github.com/terryqj0107/RiSAWOZ
공식 코드https://github.com/terryyz/ice-score
공식 코드ICE-Score: Instructing Large Language Models to Evaluate Code
https://github.com/terryyz/llm-code-eval
공식 코드ICE-Score: Instructing Large Language Models to Evaluate Code
https://github.com/textdetox/multilingual_explainable_paradetox
공식 코드Multilingual and Explainable Text Detoxification with Parallel Corpora
https://github.com/textshuttle/exploiting-bias-to-debias
공식 코드Exploiting Biased Models to De-bias Text: A Gender-Fair Rewriting Model
https://github.com/tgisaturday/L-Verse
공식 코드https://github.com/the-finai/pixiu
공식 코드FinBen: A Holistic Financial Benchmark for Large Language Models
https://github.com/themendu/TowardsSaferPretraining
공식 코드https://github.com/theohsiung/syntxt-gen
공식 코드https://github.com/thestephencasper/latent_adversarial_training
공식 코드Defending Against Unforeseen Failure Modes with Latent Adversarial Training
https://github.com/thomasscialom/beametrics
공식 코드BEAMetrics: A Benchmark for Language Generation Evaluation Evaluation
https://github.com/thompsonb/prism
공식 코드https://github.com/thorhildurt/dynamic-human-evaluation
공식 코드https://github.com/thu-coai/CDial-GPT
공식 코드https://github.com/thu-coai/CommonsenseStoryGen
공식 코드A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation
https://github.com/thu-coai/HINT
공식 코드Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence
https://github.com/thu-coai/JointGT
공식 코드JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
https://github.com/thu-coai/LOT-LongLM
공식 코드LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation
https://github.com/thu-coai/NAST
공식 코드NAST: A Non-Autoregressive Generator with Word Alignment for Unsupervised Text Style Transfer
https://github.com/thu-coai/OpenMEVA
공식 코드OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics
https://github.com/thu-coai/UNION
공식 코드UNION: An Unreferenced Metric for Evaluating Open-ended Story Generation
https://github.com/thu-coai/augesc
공식 코드AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation
https://github.com/thu-coai/characterglm-6b
공식 코드CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models
https://github.com/thu-coai/conper
공식 코드Persona-Guided Planning for Controlling the Protagonist's Persona in Story Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.