https://github.com/hengyicai/ContrastiveLearning4Dialogue
공식 코드Group-wise Contrastive Learning for Neural Dialogue Generation
Papers with Code 아카이브
Text Generation
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- 평가표
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- 보존된 평가 기록
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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/henryhzy/vl-pet
공식 코드VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control
https://github.com/heraclex12/Viwiki-spelling
공식 코드Hierarchical Transformer Encoders for Vietnamese Spelling Correction
https://github.com/hestiasky/e4srec
공식 코드https://github.com/heyjing/srlscore
공식 코드Evaluating Factual Consistency of Texts with Semantic Role Labeling
https://github.com/hf-lin/ChatMusician
공식 코드ChatMusician: Understanding and Generating Music Intrinsically with LLM
https://github.com/hgroener/diversity_in_poetry_generation
공식 코드https://github.com/hhexiy/pungen
공식 코드https://github.com/hitsz-tmg/multimodal-in-context-tuning
공식 코드A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generation
https://github.com/hiyouga/llama-factory
공식 코드LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
https://github.com/hkbunlp/explainhm-www2024
공식 코드Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models
https://github.com/hkunlp/reparam-discrete-diffusion
공식 코드A Reparameterized Discrete Diffusion Model for Text Generation
https://github.com/hkust-knowcomp/knowledge-constrained-decoding
공식 코드KCTS: Knowledge-Constrained Tree Search Decoding with Token-Level Hallucination Detection
https://github.com/hlt-mt/fbk-fairseq
공식 코드SPES: Spectrogram Perturbation for Explainable Speech-to-Text Generation
https://github.com/hltchkust/vg-gplms
공식 코드Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization
https://github.com/hmarkc/parallel-prompt-decoding
공식 코드Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference
https://github.com/hmc-cs-mdrissi/fairseq
공식 코드https://github.com/hmrishavbandy/flipsketch
공식 코드FlipSketch: Flipping Static Drawings to Text-Guided Sketch Animations
https://github.com/hnam-1765/writevit
공식 코드WriteViT: Handwritten Text Generation with Vision Transformer
https://github.com/hoangthangta/stsm
공식 코드https://github.com/holi-lab/tooldial
공식 코드ToolDial: Multi-turn Dialogue Generation Method for Tool-Augmented Language Models
https://github.com/holistic-ai/THaMES
공식 코드THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models
https://github.com/homealim2012/QE_Mani_Summary
공식 코드Using Query Expansion in Manifold Ranking for Query-Oriented Multi-Document Summarization
https://github.com/homzer/q-rm
공식 코드Discriminative Policy Optimization for Token-Level Reward Models
https://github.com/honee-w/u-sam
공식 코드U-SAM: An audio language Model for Unified Speech, Audio, and Music Understanding
https://github.com/hongbinye/cognitive-mirage-hallucinations-in-llms
공식 코드Cognitive Mirage: A Review of Hallucinations in Large Language Models
https://github.com/hongyuanluke/pcc
공식 코드PCC: Paraphrasing with Bottom-k Sampling and Cyclic Learning for Curriculum Data Augmentation
https://github.com/horseee/llm-pruner
공식 코드LLM-Pruner: On the Structural Pruning of Large Language Models
https://github.com/hqsiswiliam/SPT
공식 코드Selective Prompting Tuning for Personalized Conversations with LLMs
https://github.com/hqsiswiliam/lapdog
공식 코드Learning Retrieval Augmentation for Personalized Dialogue Generation
https://github.com/hqsiswiliam/persona-adaptive-attention
공식 코드Personalized Dialogue Generation with Persona-Adaptive Attention
https://github.com/hrashkin/plotmachines
공식 코드PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
https://github.com/htsucml/VQAG
공식 코드End-to-End Video Question-Answer Generation with Generator-Pretester Network
https://github.com/huangshulin123/blessing-generation
공식 코드Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation
https://github.com/huashen218/llm-deepfake-human-study
공식 코드Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts?
https://github.com/huawei-lin/uniguardian
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.