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Showing 3251–3275 of 10752 papers

TitleStatusHype
Cross-Sentence N-ary Relation Extraction with Graph LSTMs—0
Do You See What I Mean? Visual Resolution of Linguistic Ambiguities—0
DP-KB: Data Programming with Knowledge Bases Improves Transformer Fine Tuning for Answer Sentence Selection—0
Analyzing Sentiment Polarity Reduction in News Presentation through Contextual Perturbation and Large Language Models—0
Cross-Sentence N-ary Relation Extraction using Lower-Arity Universal Schemas—0
DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension—0
Cross Sentence Inference for Process Knowledge—0
At Which Level Should We Extract? An Empirical Analysis on Extractive Document Summarization—0
Announcing Prague Czech-English Dependency Treebank 2.0—0
drsphelps at SemEval-2022 Task 2: Learning idiom representations using BERTRAM—0
Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation—0
Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers—0
Enhancing Document-level Translation of Large Language Model via Translation Mixed-instructions—0
DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion—0
BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation—0
DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction—0
A NON-LINEAR THEORY FOR SENTENCE EMBEDDING—0
DSim, a Danish Parallel Corpus for Text Simplification—0
DSLR: Document Refinement with Sentence-Level Re-ranking and Reconstruction to Enhance Retrieval-Augmented Generation—0
DSS: Text Similarity Using Lexical Alignments of Form, Distributional Semantics and Grammatical Relations—0
DTATG: An Automatic Title Generator based on Dependency Trees—0
DTGAN: Dual Attention Generative Adversarial Networks for Text-to-Image Generation—0
DT-Neg: Tutorial Dialogues Annotated for Negation Scope and Focus in Context—0
DT\_Team at SemEval-2017 Task 1: Semantic Similarity Using Alignments, Sentence-Level Embeddings and Gaussian Mixture Model Output—0
Analyzing Political Bias in LLMs via Target-Oriented Sentiment Classification—0
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