Papers by Kai Golan Hashiloni
ID10M-JAM: Stress-Testing Idiom Identification Under Challenging Context (2026.findings-acl)
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| Challenge: | Large language models (LLMs) achieve strong performance on idiom identification benchmarks, yet their robustness to misleading contextual signals remains largely untested. |
| Approach: | They propose an adversarial extension of the ID10M dataset that jams idiom understanding by injecting coherent but conflicting context before each target sentence. |
| Outcome: | The proposed benchmark exposes systematic vulnerabilities in LLMs’ contextual reasoning, pushing idiom identification to its breaking point. |
Easy as PIE? Identifying Multi-Word Expressions with LLMs (2025.emnlp-main)
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| Challenge: | Multiword expressions (MWEs) are a semantically non-compositional subclass of multiword expression . authors show that prompt-based LLMs can perform competitively with supervised models . |
| Approach: | They propose a prompt-based approach to identify idiomatic expressions in running text . they find prompt-driven LLMs can perform competitively with supervised models . |
| Outcome: | The proposed approach can perform well with supervised models on annotated data. |