Papers by Reza Esfandiarpoor
If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions (2024.emnlp-main)
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| Challenge: | Recent studies assume that VLMs prioritize visual attributes to represent concepts. |
| Approach: | They propose a novel approach to characterize features important for VLMs using reinforcement learning. |
| Outcome: | The proposed approach characterizes features that are important for VLMs . it shows that spurious descriptions have a major role in VLM representations despite providing no helpful information. |
Trove: A Flexible Toolkit for Dense Retrieval (2026.eacl-demo)
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| Challenge: | Existing retrieval tools require considerable engineering effort for many tasks like efficient data management or model customization. |
| Approach: | They propose a novel open-source retrieval toolkit that simplifies research experiments without sacrificing flexibility or speed. |
| Outcome: | The proposed tool reduces memory consumption by 2.6 and allows for arbitrary customizations. |
Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance (2025.findings-emnlp)
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| Challenge: | a new approach to training with binary relevance labels uses synthetic data . contrastive learning with binary correlations leaves out subtle nuances useful for ranking . |
| Approach: | They propose to use waterstein distance as a loss function for training transformer-based retrievers with graduated relevance labels instead of real documents. |
| Outcome: | The proposed method outperforms conventional training with InfoNCE by a large margin on MARCO and BEIR benchmarks without using real documents. |