Papers by Adi Simhi

2 papers
Interpreting Embedding Spaces by Conceptualization (2023.emnlp-main)

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Challenge: Recent advances in large language models have a significant drawback: they are incomprehensible to humans.
Approach: They propose a method for understanding embeddings by transforming a latent embeddable space into a comprehensible conceptual space.
Outcome: The proposed method compares the semantics of the original latent embedding space to the semantic of the vectors.
Trust Me, I’m Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer (2025.findings-emnlp)

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Challenge: Prior work on large language model (LLM) hallucinations associated with model uncertainty or inaccurate knowledge.
Approach: They define and investigate a type of hallucination where a model can answer a question correctly but a perturbation causes it to produce a hallucinous response with high certainty.
Outcome: The proposed mitigations outperform existing methods on CHOKE hallucinations . the findings highlight the need to understand their origins and improve mitigation strategies .

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