Papers by Ekin Akyürek

2 papers
Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks (2024.naacl-long)

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Challenge: Recent language models possess impressive performance across a wide range of tasks . however, they often rely on narrow, non-transferable procedures for task-solving .
Approach: They propose to evaluate language models using "counterfactual" task variants that deviate from standard tasks.
Outcome: The proposed framework shows that language models perform better on a wide range of tasks compared to the default conditions.
Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability (2024.findings-acl)

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Challenge: Existing language models (LMs) generate factually correct text and estimate truth values of individual claims, but they do not reflect a coherent, manipulable model of the world.
Approach: They propose a method that uses language models to identify implications of (and contradictions within) the text they generate.
Outcome: The proposed method improves LM factuality by 3-26% across the CREAK, MQuAKE, and Reversal Curse datasets.

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