---
title: "Who cites Harnessing the linguistic signal to predict…"
description: "The papers of the Elamur Research library that cite «Harnessing the linguistic signal to predict scalar inferences», found in their bibliographies."
canonical: "https://research.elamur.ai/free/en/papers/schuster-2020-harnessing-linguistic-signal-predict-scalar/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Harnessing the linguistic signal to predict…](https://md.research.elamur.ai/free/en/papers/schuster-2020-harnessing-linguistic-signal-predict-scalar/) / cited by

# Who cites «Harnessing the linguistic signal to predict scalar inferences»

30 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/schuster-2020-harnessing-linguistic-signal-predict-scalar/)

1. [CrosSing: Cross-Scale Reasoning Evaluation on LLMs against Humans](https://aclanthology.org/2026.scil-main.36/) *— 2026 · Proceedings of the Society for Computation in Linguistics 2026*
2. [DRInQ: Evaluating Conversational Implicature with Controlled Context Variation](https://aclanthology.org/2026.acl-long.1597/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://aclanthology.org/2026.conll-main.15/) *— 2026 · Proceedings of the 30th Conference on Computational Natural Language Learning*
4. [Understand the Implication: Learning to Think for Pragmatic Understanding](https://aclanthology.org/2025.findings-acl.1218/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
5. [Experimental Pragmatics with Machines: Testing LLM Predictions for the Inferences of Plain and Embedded Disjunctions](https://arxiv.org/abs/2405.05776) *— 2024 · arXiv:2405.05776*
6. [PUB: A Pragmatics Understanding Benchmark for Assessing LLMs” Pragmatics Capabilities](https://md.research.elamur.ai/free/en/papers/sravanthi-2024-pub-pragmatics-understanding-benchmark-assessing/) *— our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
7. [Pragmatic inference of scalar implicature by LLMs](https://aclanthology.org/2024.acl-srw.2/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
8. [Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering](https://aclanthology.org/2024.naacl-long.403/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
9. [Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics](https://aclanthology.org/2024.lrec-main.1141/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
10. [SIGA: A Naturalistic NLI Dataset of English Scalar Implicatures with Gradable Adjectives](https://md.research.elamur.ai/free/en/papers/nizamani-2024-siga-naturalistic-nli-dataset-english/) *— our card · 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
11. [A fine-grained comparison of pragmatic language understanding in humans and language models](https://md.research.elamur.ai/free/en/papers/hu-2023-fine-grained-comparison-pragmatic-language/) *— our card · 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
12. [Expectations over Unspoken Alternatives Predict Pragmatic Inferences](https://md.research.elamur.ai/free/en/papers/hu-2023-expectations-over-unspoken-alternatives-predict/) *— our card · 2023*
13. [Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://aclanthology.org/2023.findings-emnlp.840/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
14. [Representation of Lexical Stylistic Features in Language Models' Embedding Space](https://aclanthology.org/2023.starsem-1.32/) *— 2023 · Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)*
15. [ANLIzing the Adversarial Natural Language Inference Dataset](https://aclanthology.org/2022.scil-1.3/) *— 2022 · Proceedings of the Society for Computation in Linguistics 2022*
16. [Incremental Processing of Principle B: Mismatches Between Neural Models and Humans](https://aclanthology.org/2022.conll-1.11/) *— 2022 · Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)*
17. [Investigating the Performance of Transformer-Based NLI Models on Presuppositional Inferences](https://aclanthology.org/2022.coling-1.65/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
18. [Pre-trained Language Models” Interpretation of Evaluativity Implicature: Evidence from Gradable Adjectives Usage in Context](https://aclanthology.org/2022.unimplicit-1.1/) *— 2022 · Proceedings of the Second Workshop on Understanding Implicit and Underspecified Language*
19. [Psycholinguistic Diagnosis of Language Models' Commonsense Reasoning](https://aclanthology.org/2022.csrr-1.3/) *— 2022 · Proceedings of the First Workshop on Commonsense Representation and Reasoning (CSRR 2022)*
20. [The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs](https://arxiv.org/abs/2210.14986) *— 2022 · arXiv:2210.14986*
21. [The Viability of Best-worst Scaling and Categorical Data Label Annotation Tasks in Detecting Implicit Bias](https://aclanthology.org/2022.nlperspectives-1.5/) *— 2022 · Proceedings of the 1st Workshop on Perspectivist Approaches to NLP @LREC2022*
22. [Dynabench: Rethinking Benchmarking in NLP](https://aclanthology.org/2021.naacl-main.324/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
23. [He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics](https://md.research.elamur.ai/free/en/papers/jiang-2021-he-thinks-he-knows-better/) *— our card · 2021*
24. [Learning to Recognize Dialect Features](https://aclanthology.org/2021.naacl-main.184/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
25. [NOPE: A Corpus of Naturally-Occurring Presuppositions in English](https://md.research.elamur.ai/free/en/papers/parrish-2021-nope-corpus-naturally-occurring-presuppositions/) *— our card · 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning*
26. [Predicting pragmatic discourse features in the language of adults with autism spectrum disorder](https://aclanthology.org/2021.acl-srw.29/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop*
27. [Predicting scalar inferences from “or” to “not both” using neural sentence encoders](https://md.research.elamur.ai/free/en/papers/li-2021-predicting-scalar-inferences-or-not/) *— our card · 2021 · Proceedings of the Society for Computation in Linguistics 2021*
28. [Uncovering Constraint-Based Behavior in Neural Models via Targeted Fine-Tuning](https://aclanthology.org/2021.acl-long.93/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
29. [Discourse structure interacts with reference but not syntax in neural language models](https://aclanthology.org/2020.conll-1.32/) *— 2020 · Proceedings of the 24th Conference on Computational Natural Language Learning*
30. [Explaining the Trump Gap in Social Distancing Using COVID Discourse](https://aclanthology.org/2020.nlpcovid19-2.10/) *— 2020 · Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020*