Papers by Deniz Yuret
Neurocache: Efficient Vector Retrieval for Long-range Language Modeling (2024.naacl-long)
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| Challenge: | Recent research shows that retrieval-augmented models with shorter contexts (4K tokens) can match the performance of models with longer contexts (16K/32K token) |
| Approach: | They introduce an approach to extend the effective context size of large language models by using an external vector cache to store past states. |
| Outcome: | The proposed method improves on models trained from scratch and pre-trained models. |
CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions (2022.findings-acl)
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Tayfun Ates, M. Ateşoğlu, Çağatay Yiğit, Ilker Kesen, Mert Kobas, Erkut Erdem, Aykut Erdem, Tilbe Goksun, Deniz Yuret
| Challenge: | Existing models with similar physical and causal understanding capabilities are still underdeveloped. |
| Approach: | They propose a video question answering dataset that requires causal reasoning about physical forces and object interactions. |
| Outcome: | The proposed dataset requires causal reasoning about physical forces and object interactions. |
Mukayese: Turkish NLP Strikes Back (2022.findings-acl)
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| Challenge: | Having sufficient resources for language X lifts it from the under-resourced languages class, but not necessarily from the researched class. |
| Approach: | They propose a set of NLP benchmarks for the Turkish language that contains several NLP tasks. |
| Outcome: | The proposed benchmarks outperform previous work significantly in the Turkish language. |
Sequential Compositional Generalization in Multimodal Models (2024.naacl-long)
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| Challenge: | a growing number of multimodal models have a limited capacity for generalization . however, prior studies into compositionality have focused on visual grounding and downstream tasks like image captioning. |
| Approach: | They examine compositional generalization using egocentric kitchen activity videos . they find bi-modal and tri-modal models exhibit a clear edge over their text-only counterparts . |
| Outcome: | The proposed model outperforms text-only models in a multimodal setting. |