https://github.com/cindyxinyiwang/deep-latent-sequence-model
공식 코드A Probabilistic Formulation of Unsupervised Text Style Transfer
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/circle-ming/multicsr
공식 코드https://github.com/cissyduan/query_variant_ad
공식 코드Query-Variant Advertisement Text Generation with Association Knowledge
https://github.com/citymind-lab/urbanvlp
공식 코드UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction
https://github.com/ckdjrkffz/controlling_keyword_position
공식 코드https://github.com/cl-tohoku/eval-via-selection
공식 코드Evaluating Dialogue Generation Systems via Response Selection
https://github.com/claire874/gloss-free-mlslt
공식 코드Multilingual Gloss-free Sign Language Translation: Towards Building a Sign Language Foundation Model
https://github.com/claude-liu/relm
공식 코드https://github.com/clear-nus/DGflow
공식 코드Refining Deep Generative Models via Discriminator Gradient Flow
https://github.com/clement1290/chatgpt-detection-pr-hppt
공식 코드Is ChatGPT Involved in Texts? Measure the Polish Ratio to Detect ChatGPT-Generated Text
https://github.com/cleolotta/fair-and-private-lm
공식 코드Trade-Offs Between Fairness and Privacy in Language Modeling
https://github.com/clips/clinspell
공식 코드https://github.com/cliveyn/pdsum
공식 코드PDSum: Prototype-driven Continuous Summarization of Evolving Multi-document Sets Stream
https://github.com/cloudygoose/blindspot_nlg
공식 코드On the Blind Spots of Model-Based Evaluation Metrics for Text Generation
https://github.com/clubiedong/kvcachequantization
공식 코드https://github.com/cluebbers/dpo-rlhf-paraphrase-types
공식 코드Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF Evaluated with Human-Ranked Data
https://github.com/codelion/optillm
공식 코드Eliciting Fine-Tuned Transformer Capabilities via Inference-Time Techniques
https://github.com/codezakh/exploiting-BERT-thru-translation
공식 코드Exploiting BERT For Multimodal Target Sentiment Classification Through Input Space Translation
https://github.com/codinnlg/bridge_gap_diffusion
공식 코드https://github.com/codium-ai/alphacodium
공식 코드Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering
https://github.com/cods-gcs/chatty-gen
공식 코드Dialogue Benchmark Generation from Knowledge Graphs with Cost-Effective Retrieval-Augmented LLMs
https://github.com/cods-gcs/kgqan
공식 코드A Universal Question-Answering Platform for Knowledge Graphs
https://github.com/coleygroup/graph2smiles
공식 코드https://github.com/collinzrj/adversarial_decoding
공식 코드Adversarial Decoding: Generating Readable Documents for Adversarial Objectives
https://github.com/complementizer/wcep-mds-dataset
공식 코드A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal
https://github.com/composable-models/llm_multiagent_debate
공식 코드Improving Factuality and Reasoning in Language Models through Multiagent Debate
https://github.com/computationalmedia/supmmd
공식 코드SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy
https://github.com/cong-zeng/dald
공식 코드DALD: Improving Logits-based Detector without Logits from Black-box LLMs
https://github.com/congboma/disentanglesum
공식 코드Disentangling Specificity for Abstractive Multi-document Summarization
https://github.com/controllability/jailbreak-evaluation
공식 코드https://github.com/cookielee77/DAST
공식 코드https://github.com/cornell-rl/tril
공식 코드https://github.com/coswindywang/HdLM
공식 코드Making Language Model a Hierarchical Classifier and Generator
https://github.com/coszero/TabIS
공식 코드Uncovering Limitations of Large Language Models in Information Seeking from Tables
https://github.com/cps11/catvrnn
공식 코드https://github.com/cps11/darl
공식 코드Reinforcement Learning for Few-Shot Text Generation Adaptation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.