{"total":56,"rows":[{"id":"2303.13809","title":"Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models","created":"2023-03-24","cited_by_count":87,"area":null},{"id":"2204.09269","title":"A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond","created":"2022-04-20","cited_by_count":64,"area":null},{"id":"2106.05093","title":"Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation","created":"2021-06-09","cited_by_count":57,"area":null},{"id":"2205.07459","title":"Directed Acyclic Transformer for Non-Autoregressive Machine Translation","created":"2022-05-16","cited_by_count":44,"area":null},{"id":"2402.11890","title":"Revisiting Knowledge Distillation for Autoregressive Language Models","created":"2024-02-19","cited_by_count":42,"area":"distill"},{"id":"2106.00903","title":"Rejuvenating Low-Frequency Words: Making the Most of Parallel Data in Non-Autoregressive Translation","created":"2021-06-02","cited_by_count":34,"area":"distill"},{"id":"2208.10160","title":"PANDA: Prompt Transfer Meets Knowledge Distillation for Efficient Model Adaptation","created":"2022-08-22","cited_by_count":31,"area":"distill"},{"id":"2508.08712","title":"A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models","created":"2025-08-12","cited_by_count":30,"area":"diffusion"},{"id":"2207.11681","title":"Learning Graph Neural Networks for Image Style Transfer","created":"2022-07-24","cited_by_count":29,"area":null},{"id":"2310.09762","title":"Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer","created":"2023-10-15","cited_by_count":29,"area":"moe"},{"id":"2104.06457","title":"Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation","created":"2021-04-13","cited_by_count":28,"area":"distill"},{"id":"2206.05975","title":"On the Learning of Non-Autoregressive Transformers","created":"2022-06-13","cited_by_count":27,"area":null},{"id":"2106.05546","title":"Progressive Multi-Granularity Training for Non-Autoregressive Translation","created":"2021-06-10","cited_by_count":25,"area":null},{"id":"2311.03127","title":"Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs","created":"2023-11-06","cited_by_count":25,"area":null},{"id":"2308.12898","title":"Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?","created":"2023-08-24","cited_by_count":21,"area":"mllm"},{"id":"2412.12639","title":"Falcon: Faster and Parallel Inference of Large Language Models through Enhanced Semi-Autoregressive Drafting and Custom-Designed Decoding Tree","created":"2024-12-17","cited_by_count":20,"area":"inference"},{"id":"2109.07780","title":"Improving Neural Machine Translation by Bidirectional Training","created":"2021-09-16","cited_by_count":17,"area":null},{"id":"2211.13490","title":"Pose-disentangled Contrastive Learning for Self-supervised Facial Representation","created":"2022-11-24","cited_by_count":17,"area":null},{"id":"2401.06659","title":"WisdoM: Improving Multimodal Sentiment Analysis by Fusing Contextual World Knowledge","created":"2024-01-12","cited_by_count":16,"area":null},{"id":"2203.08442","title":"Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation","created":"2022-03-16","cited_by_count":14,"area":null},{"id":"2207.01426","title":"Dynamic Contrastive Distillation for Image-Text Retrieval","created":"2022-07-04","cited_by_count":14,"area":null},{"id":"2212.01188","title":"Improving Simultaneous Machine Translation with Monolingual Data","created":"2022-12-02","cited_by_count":13,"area":"distill"},{"id":"2403.09963","title":"Take Care of Your Prompt Bias! Investigating and Mitigating Prompt Bias in Factual Knowledge Extraction","created":"2024-03-15","cited_by_count":13,"area":null},{"id":"2105.12900","title":"How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation?","created":"2021-05-27","cited_by_count":12,"area":"distill"},{"id":"2404.14827","title":"Sentence-Level or Token-Level? A Comprehensive Study on Knowledge Distillation","created":"2024-04-23","cited_by_count":12,"area":"distill"},{"id":"2107.11572","title":"The USYD-JD Speech Translation System for IWSLT 2021","created":"2021-07-24","cited_by_count":11,"area":null},{"id":"2110.13398","title":"Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis","created":"2021-10-26","cited_by_count":11,"area":null},{"id":"2303.06662","title":"Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation","created":"2023-03-12","cited_by_count":11,"area":null},{"id":"2305.15273","title":"Revisiting Token Dropping Strategy in Efficient BERT Pretraining","created":"2023-05-24","cited_by_count":11,"area":"inference"},{"id":"2104.06393","title":"Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding","created":"2021-04-13","cited_by_count":9,"area":null},{"id":"2105.04475","title":"Self-Guided Curriculum Learning for Neural Machine Translation","created":"2021-05-10","cited_by_count":9,"area":null},{"id":"2209.09444","title":"Vega-MT: The JD Explore Academy Translation System for WMT22","created":"2022-09-20","cited_by_count":9,"area":null},{"id":"2304.11791","title":"Directed Acyclic Transformer Pre-training for High-quality Non-autoregressive Text Generation","created":"2023-04-24","cited_by_count":8,"area":null},{"id":"2305.15275","title":"Self-Evolution Learning for Discriminative Language Model Pretraining","created":"2023-05-24","cited_by_count":8,"area":null},{"id":"2210.11017","title":"Multi-Granularity Optimization for Non-Autoregressive Translation","created":"2022-10-20","cited_by_count":6,"area":null},{"id":"2305.02814","title":"Noise-Resistant Multimodal Transformer for Emotion Recognition","created":"2023-05-04","cited_by_count":6,"area":null},{"id":"2601.12979","title":"The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check","created":"2026-01-19","cited_by_count":6,"area":"diffusion"},{"id":"2207.04206","title":"A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation","created":"2022-07-09","cited_by_count":5,"area":null},{"id":"2303.07457","title":"AMOM: Adaptive Masking over Masking for Conditional Masked Language Model","created":"2023-03-13","cited_by_count":5,"area":null},{"id":"2304.10354","title":"Prompt-Learning for Cross-Lingual Relation Extraction","created":"2023-04-20","cited_by_count":4,"area":null},{"id":"2109.04620","title":"Rule-based Morphological Inflection Improves Neural Terminology Translation","created":"2021-09-10","cited_by_count":3,"area":null},{"id":"2111.04079","title":"Variance-Aware Machine Translation Test Sets","created":"2021-11-07","cited_by_count":3,"area":null},{"id":"2204.13355","title":"Neighbors Are Not Strangers: Improving Non-Autoregressive Translation under Low-Frequency Lexical Constraints","created":"2022-04-28","cited_by_count":3,"area":null},{"id":"2210.10416","title":"Hybrid-Regressive Neural Machine Translation","created":"2022-10-19","cited_by_count":3,"area":null},{"id":"2409.12512","title":"Exploring and Enhancing the Transfer of Distribution in Knowledge Distillation for Autoregressive Language Models","created":"2024-09-19","cited_by_count":3,"area":"distill"},{"id":"2212.10257","title":"Original or Translated? On the Use of Parallel Data for Translation Quality Estimation","created":"2022-12-20","cited_by_count":2,"area":null},{"id":"2303.00501","title":"OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System","created":"2023-03-01","cited_by_count":2,"area":null},{"id":"2303.17910","title":"Selective Knowledge Distillation for Non-Autoregressive Neural Machine Translation","created":"2023-03-31","cited_by_count":2,"area":"distill"},{"id":"2305.16155","title":"Revisiting Non-Autoregressive Translation at Scale","created":"2023-05-25","cited_by_count":2,"area":null},{"id":"2309.16599","title":"Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation","created":"2023-09-28","cited_by_count":2,"area":null},{"id":"2602.15845","title":"KD4MT: A Survey of Knowledge Distillation for Machine Translation","created":"2026-01-22","cited_by_count":2,"area":"distill"},{"id":"2205.11162","title":"A Self-Paced Mixed Distillation Method for Non-Autoregressive Generation","created":"2022-05-23","cited_by_count":1,"area":null},{"id":"2405.12788","title":"What Have We Achieved on Non-autoregressive Translation?","created":"2024-05-21","cited_by_count":1,"area":null},{"id":"2509.24638","title":"Hype or not? Formalizing Automatic Promotional Language Detection in Biomedical Research","created":"2025-09-29","cited_by_count":0,"area":null},{"id":"2601.22546","title":"Towards the Holographic Characteristic of LLMs for Efficient Short-text Generation","created":"2026-01-30","cited_by_count":0,"area":"lr"},{"id":"2609.31871","title":"IndustryLLM: Failure-Driven LLM Training for Industrial Procurement","created":"2026-09-25","cited_by_count":0,"area":null}],"next_cursor":null}