Papers by Noam Kahlon
Small Models, Big Results: Achieving Superior Intent Extraction through Decomposition (2025.emnlp-main)
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Danielle Cohen, Yoni Halpern, Noam Kahlon, Joel Oren, Omri Berkovitch, Sapir Caduri, Ido Dagan, Anatoly Efros
| Challenge: | Large multi-modal large language models are good at extracting user intents from UI sequences, but smaller models struggle with accurate intent inference. |
| Approach: | They propose a decomposed approach for extracting user intent from small models . they perform structured interaction summarization and intent extraction using a fine-tuned model . |
| Outcome: | The proposed method surpasses the performance of large MLLMs in the intent extraction task. |
Dyna-bAbI: unlocking bAbI’s potential with dynamic synthetic benchmarking (2022.starsem-1)
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Ronen Tamari, Kyle Richardson, Noam Kahlon, Aviad Sar-shalom, Nelson F. Liu, Reut Tsarfaty, Dafna Shahaf
| Challenge: | Controlled synthetic tasks are an important resource for diagnosing model behavior. |
| Approach: | They propose a framework that provides fine-grained control over task generation in bAbI. |
| Outcome: | The proposed framework provides fine-grained control over task generation in the bAbI benchmark. |