activity
20152026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 621 across the 33 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

cs.CL2024★ 1 cited

From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization

Catarina G. Belem, Pouya Pezeshkpour, Hayate Iso +3

Although many studies have investigated and reduced hallucinations in large language models (LLMs) for single-document tasks, research on hallucination in multi-document summarizat…

cs.DB2024★ 1 cited

A Blueprint Architecture of Compound AI Systems for Enterprise

Eser Kandogan, Sajjadur Rahman, Nikita Bhutani +11

Large Language Models (LLMs) have showcased remarkable capabilities surpassing conventional NLP challenges, creating opportunities for use in production use cases. Towards this goa…

cs.CL2024

LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs

Arash Gholami Davoodi, Seyed Pouyan Mousavi Davoudi, Pouya Pezeshkpour

Large language models (LLMs) demonstrate impressive capabilities in mathematical reasoning. However, despite these achievements, current evaluations are mostly limited to specific…

cs.CL2024

Multi-Conditional Ranking with Large Language Models

Pouya Pezeshkpour, Estevam Hruschka

Utilizing large language models (LLMs) to rank a set of items has become a common approach in recommendation and retrieval systems. Typically, these systems focus on ordering a sub…

cs.CL2024★ 2 cited

Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions

Pouya Pezeshkpour, Eser Kandogan, Nikita Bhutani +3

Remarkable performance of large language models (LLMs) in a variety of tasks brings forth many opportunities as well as challenges of utilizing them in production settings. Towards…