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Methodology
← Understanding
Natural Language Processing
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Understanding
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Semantic Analysis
2901 directly classified papers
Papers per year
2005: 1
2006: 1
2008: 1
2009: 2
2010: 3
2011: 1
2012: 1
2013: 3
2015: 2
2016: 37
2017: 150
2018: 153
2019: 250
2020: 310
2021: 378
2022: 361
2023: 380
2024: 403
2025: 402
2026: 62
Papers
Chain-of-Thought Tuning: Masked Language Models can also Think Step By Step in Natural Language Understanding
EMNLP 2023
Guiding AMR Parsing with Reverse Graph Linearization
EMNLP 2023
From the One, Judge of the Whole: Typed Entailment Graph Construction with Predicate Generation
ACL 2023
Entity Tracking in Language Models
ACL 2023
Learning to Substitute Spans towards Improving Compositional Generalization
ACL 2023
MISGENDERED: Limits of Large Language Models in Understanding Pronouns
ACL 2023
Quantifying the redundancy between prosody and text
EMNLP 2023
PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question Answering
EMNLP 2023
Improving Language Models’ Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary
EMNLP 2023
No clues, good clues: Out of context Lexical Relation Classification
ACL 2023
This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models
EMNLP 2023
Systematic word meta-sense extension
EMNLP 2023
Construction Artifacts in Metaphor Identification Datasets
EMNLP 2023
Modeling Empathic Similarity in Personal Narratives
EMNLP 2023
Modeling Conceptual Attribute Likeness and Domain Inconsistency for Metaphor Detection
EMNLP 2023
APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning
ACL 2023
M3Seg: A Maximum-Minimum Mutual Information Paradigm for Unsupervised Topic Segmentation in ASR Transcripts
EMNLP 2023
Explaining with Contrastive Phrasal Highlighting: A Case Study in Assisting Humans to Detect Translation Differences
EMNLP 2023
GeoLM: Empowering Language Models for Geospatially Grounded Language Understanding
EMNLP 2023
Prompting is not a substitute for probability measurements in large language models
EMNLP 2023
Elaborative Simplification as Implicit Questions Under Discussion
EMNLP 2023
Variance Matters: Detecting Semantic Differences without Corpus/Word Alignment
EMNLP 2023
Automatic Debate Evaluation with Argumentation Semantics and Natural Language Argument Graph Networks
EMNLP 2023
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding
AAAI 2023
Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?
EMNLP 2023
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