Dagan et al. 2018; Tsuchiya 2018; Belinkov et al. Hypothesis-only baselines • In his project for this course (2016), Leonid Keselman observed that hypothesis-only models are strong. We use the Multi-Genre Natural Language Inference Corpus (MNLI), which provides training examples from multiple domains (transcribed speech, popular fiction, …

We evaluate whether adversarial learning can be used in NLI to encourage models to learn representations free of hypothesis-only biases. Especially when an NLI dataset assumes inference is occurring based purely on the relationship between a context and a hypothesis, it follows that assessing entailment relations while ignoring the provided context is a degenerate solution. Stanford University Stanford. The corpus is made to evaluate how to perform inference in any language (including low-resources ones like Swahili or Urdu) when only English NLI data is available at training time. We propose a hypothesis only baseline for diagnosing Natural Language Inference (NLI).

Hypothesis only baselines in natural language inference. In this work, we manage to derive adversarial examples in terms of the hypothesis-only bias and explore eligible ways to mitigate such bias.

Abstract: Add/Edit. We propose a hypothesis only baseline for diagnosing Natural Language Inference (NLI). In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, pages 180–191. Because of the large magnitude of these biases, confirmed On the other hand, examples where this … Rimell and Clark (2010) Laura Rimell and Stephen Clark. Poliak et al. Our analyses indicate that the representations … 2010. 2018. • Other groups have since further supported this (Poliak et al.

2018; Gururangan et al. Perspectives • Zaenen et al. ... Hypothesis only baselines in natural language inference. Natural Language Inference (NLI) models receive two input sentences: a premise and a hypothesis. Natural language inference. Abstract: Add/Edit. • Emphasis on variability of linguistic expression. Association for Computational Linguistics . @inproceedings{hypothsesis-only-nli-baselines, author = {Poliak, Adam and Naradowsky, Jason and Haldar, Aparajita and Rudinger, Rachel and {Van Durme}, Benjamin}, title = {Hypothesis Only Baselines for Natural Language Inference}, booktitle = {The Seventh Joint Conference on Lexical and Computational Semantics (*SEM)}, year = {2018} } In this work, we manage to derive adversarial examples in terms of the hypothesis-only bias and explore eligible ways to mitigate such bias. Popular Natural Language Inference (NLI) datasets have been shown to be tainted by hypothesis-only biases. We present a new logic-based inference engine for natural language inference (NLI) called MonaLog, which is based on natural logic and the monotonicity calculus. Association for Computational Linguistics New Orleans, Louisiana conference publication We propose a hypothesis only baseline for diagnosing Natural Language Inference (NLI).

Because of the large magnitude of these biases, confirmed • Commonsense reasoning, rather than strict logic. Especially when an NLI dataset assumes inference is occurring based purely on the relationship between a context and a hypothesis, it follows that assessing entailment relations while ignoring the provided context is a degenerate solution. Many recent studies have shown that for models trained on datasets for natural language inference (NLI), it is possible to make correct predictions by merely looking at the hypothesis while completely ignoring the premise.

In contrast to existing logic-based approaches, our system is intentionally designed to be as lightweight as possible, and operates using a small set of well-known (surface-level) monotonicity facts about quantifiers, lexical items and …

Abstract: Many recent studies have shown that for models trained on datasets for natural language inference (NLI), it is possible to make correct predictions by merely looking at the hypothesis while completely ignoring the premise. Natural language inference (NLI) is the problem of determining whether from a premise sentence P one can infer another hypothesis sentence H [MacCartney2009] NLI is a fundamentally important problem that has applications in many tasks including question … Especially when an NLI dataset assumes infer-ence is occurring based purely on the relation-ship between a context and a hypothesis, it fol-lows that assessing entailment relations while ignoring the provided context is a degenerate solution. Association for Computational Linguistics. One solution is cross-lingual … In this work, we manage to derive adversarial examples in terms of the hypothesis-only bias and explore eligible ways to mitigate such bias. These artefacts are exploited by neural networks even when only considering the hypothesis and ignoring the premise, leading to unwanted biases. Especially when an NLI dataset assumes inference is occurring based purely on the relationship between a context and a hypothesis, it follows that assessing entailment relations while ignoring the provided context is a degenerate solution.

Abstract We propose a hypothesis only baseline for diagnosing Natural Language Inference (NLI). Does the premise justify an inference to the hypothesis?



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