{"total":24,"rows":[{"id":"2203.10929","title":"General and Domain Adaptive Chinese Spelling Check with Error Consistent Pretraining","created":"2022-03-21","cited_by_count":25,"area":null},{"id":"2206.05395","title":"Why is constrained neural language generation particularly challenging?","created":"2022-06-11","cited_by_count":19,"area":null},{"id":"2305.01181","title":"A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models","created":"2023-05-02","cited_by_count":19,"area":null},{"id":"2108.04543","title":"Known Operator Learning and Hybrid Machine Learning in Medical Imaging -- A Review of the Past, the Present, and the Future","created":"2021-08-10","cited_by_count":18,"area":null},{"id":"2106.03730","title":"Encouraging Neural Machine Translation to Satisfy Terminology Constraints","created":"2021-06-07","cited_by_count":10,"area":null},{"id":"2403.01196","title":"Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021","created":"2024-03-02","cited_by_count":9,"area":null},{"id":"2102.10160","title":"Multi-Domain Adaptation in Neural Machine Translation Through Multidimensional Tagging","created":"2021-02-19","cited_by_count":8,"area":null},{"id":"2106.12398","title":"End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages","created":"2021-06-23","cited_by_count":6,"area":null},{"id":"2105.05498","title":"Improving Lexically Constrained Neural Machine Translation with Source-Conditioned Masked Span Prediction","created":"2021-05-12","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":"2401.14559","title":"Language Modelling Approaches to Adaptive Machine Translation","created":"2024-01-25","cited_by_count":3,"area":null},{"id":"2507.18263","title":"Locate-and-Focus: Enhancing Terminology Translation in Speech Language Models","created":"2025-07-24","cited_by_count":3,"area":null},{"id":"2109.09350","title":"CUNI systems for WMT21: Terminology translation Shared Task","created":"2021-09-20","cited_by_count":2,"area":null},{"id":"2111.02120","title":"Lingua Custodia's participation at the WMT 2021 Machine Translation using Terminologies shared task","created":"2021-11-03","cited_by_count":2,"area":null},{"id":"2407.13164","title":"Translate-and-Revise: Boosting Large Language Models for Constrained Translation","created":"2024-07-18","cited_by_count":2,"area":null},{"id":"2107.00334","title":"Modeling Target-side Inflection in Placeholder Translation","created":"2021-07-01","cited_by_count":1,"area":null},{"id":"2204.00871","title":"Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding","created":"2022-04-02","cited_by_count":1,"area":null},{"id":"2305.17351","title":"Disambiguated Lexically Constrained Neural Machine Translation","created":"2023-05-27","cited_by_count":1,"area":null},{"id":"2308.03601","title":"Negative Lexical Constraints in Neural Machine Translation","created":"2023-08-07","cited_by_count":1,"area":null},{"id":"2111.03813","title":"Analyzing Architectures for Neural Machine Translation Using Low Computational Resources","created":"2021-11-06","cited_by_count":0,"area":null},{"id":"2205.11255","title":"A Template-based Method for Constrained Neural Machine Translation","created":"2022-05-23","cited_by_count":0,"area":null},{"id":"2209.03554","title":"Knowledge Based Template Machine Translation In Low-Resource Setting","created":"2022-09-08","cited_by_count":0,"area":null},{"id":"2508.18701","title":"Attention2Probability: Attention-Driven Terminology Probability Estimation for Robust Speech-to-Text System","created":"2025-08-26","cited_by_count":0,"area":null},{"id":"2609.03350","title":"From Zero to Hero: An Open LLM Ecosystem for Armenian","created":"2026-09-03","cited_by_count":0,"area":null}],"next_cursor":null}