16 citations · 22 across the 11 of their papers we have counts for
12 papers
Beyond Semantic Similarity: Performance and Costs of Agentic Retrieval for Complex Tasks
Reza Esfandiarpoor, Radek Osmulski, Yauhen Babakhin +8
Modern information systems, including many agentic workflows, use dense retrieval to explore large amounts of unstructured data. However, dense retrieval relies on surface-level se…
Trove: A Flexible Toolkit for Dense Retrieval
Reza Esfandiarpoor, Max Zuo, Stephen H. Bach
We introduce Trove, an easy-to-use open-source retrieval toolkit that simplifies research experiments without sacrificing flexibility or speed. For the first time, we introduce eff…
TheMCPCompany: Creating General-purpose Agents with Task-specific Tools
Reza Esfandiarpoor, Vishwas Suryanarayanan, Stephen H. Bach +2
Since the introduction of the Model Context Protocol (MCP), the number of available tools for Large Language Models (LLMs) has increased significantly. These task-specific tool set…
Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance
Reza Esfandiarpoor, George Zerveas, Ruochen Zhang +3
Although synthetic data has changed various aspects of information retrieval (IR) pipelines, the main training paradigm remains: contrastive learning with binary relevance labels,…
If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions
Reza Esfandiarpoor, Cristina Menghini, Stephen H. Bach
Recent works often assume that Vision-Language Model (VLM) representations are based on visual attributes like shape. However, it is unclear to what extent VLMs prioritize this inf…
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification
Reza Esfandiarpoor, Stephen H. Bach
A promising approach for improving the performance of vision-language models like CLIP for image classification is to extend the class descriptions (i.e., prompts) with related att…
An Adaptive Method for Weak Supervision with Drifting Data
Alessio Mazzetto, Reza Esfandiarpoor, Akash Singirikonda +2
We introduce an adaptive method with formal quality guarantees for weak supervision in a non-stationary setting. Our goal is to infer the unknown labels of a sequence of data by us…
Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks
Reza Esfandiarpoor, Amy Pu, Mohsen Hajabdollahi +1
In many practical few-shot learning problems, even though labeled examples are scarce, there are abundant auxiliary datasets that potentially contain useful information. We propose…
Multiple Abnormality Detection for Automatic Medical Image Diagnosis Using Bifurcated Convolutional Neural Network
Mohsen Hajabdollahi, Reza Esfandiarpoor, Elyas Sabeti +4
Automating classification and segmentation process of abnormal regions in different body organs has a crucial role in most of medical imaging applications such as funduscopy, endos…
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames
Mohsen Hajabdollahi, Reza Esfandiarpoor, Pejman Khadivi +4
Wireless capsule endoscopy (WCE) is an effective mean for diagnosis of gastrointestinal disorders. Detection of informative scenes in WCE video could reduce the length of transmitt…
Low complexity convolutional neural network for vessel segmentation in portable retinal diagnostic devices
M. Hajabdollahi, R. Esfandiarpoor, S. M. R. Soroushmehr +3
Retinal vessel information is helpful in retinal disease screening and diagnosis. Retinal vessel segmentation provides useful information about vessels and can be used by physician…
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization
Mohsen Hajabdollahi, Reza Esfandiarpoor, S. M. Reza Soroushmehr +3
Wireless capsule endoscopy (WCE) is an effective means of diagnosis of gastrointestinal disorders. Detection of informative scenes by WCE could reduce the length of transmitted vid…