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Showing 301–325 of 586 papers

TitleStatusHype
Don't Rank, Combine! Combining Machine Translation Hypotheses Using Quality Estimation—0
Double Retrieval and Ranking for Accurate Question Answering—0
Drowning in Documents: Consequences of Scaling Reranker Inference—0
E2LVLM:Evidence-Enhanced Large Vision-Language Model for Multimodal Out-of-Context Misinformation Detection—0
Early and Late Combinations of Criteria for Reranking Distributional Thesauri—0
EdgeRec: Recommender System on Edge in Mobile Taobao—0
Effective Inference for Generative Neural Parsing—0
Efficient Biomedical Entity Linking: Clinical Text Standardization with Low-Resource Techniques—0
Efficient Stacked Dependency Parsing by Forest Reranking—0
Efficient Title Reranker for Fast and Improved Knowledge-Intense NLP—0
Embedding-based Recommender System for Job to Candidate Matching on Scale—0
Enabling arbitrary translation objectives with Adaptive Tree Search—0
Encoding Semantic Resources in Syntactic Structures for Passage Reranking—0
End-to-end Learnable Diversity-aware News Recommendation—0
Enhancing Relevance of Embedding-based Retrieval at Walmart—0
Enhancing Tourism Recommender Systems for Sustainable City Trips Using Retrieval-Augmented Generation—0
Ensemble and Reranking: Using Multiple Models in the NICT-2 Neural Machine Translation System at WAT2017—0
Entropy and Graph Based Modelling of Document Coherence using Discourse Entities: An Application—0
RAG-Fusion: a New Take on Retrieval-Augmented Generation—0
RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis—0
RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models—0
Ranking Facts for Explaining Answers to Elementary Science Questions—0
Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference—0
Ranking Kernels for Structures and Embeddings: A Hybrid Preference and Classification Model—0
Rank It, Then Ask It: Input Reranking for Maximizing the Performance of LLMs on Symmetric Tasks—0
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