activity
20202026
most citedActive Few-Shot Learning for Text Classification

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Seq2Seq2Seq: Lossless Data Compression via Discrete Latent Transformers and Reinforcement Learning

Mahdi Khodabandeh, Ghazal Shabani, Arash Yousefi Jordehi +1

Efficient lossless compression is essential for minimizing storage costs and transmission overhead while preserving data integrity. Traditional compression techniques, such as dict…

cs.CL2025

From Semantic Roles to Opinion Roles: SRL Data Extraction for Multi-Task and Transfer Learning in Low-Resource ORL

Amirmohammad Omidi Galdiani, Sepehr Rezaei Melal, Mohammad Norasteh +2

This report presents a detailed methodology for constructing a high-quality Semantic Role Labeling (SRL) dataset from the Wall Street Journal (WSJ) portion of the OntoNotes 5.0 cor…

cs.CL2025★ 1 cited

Active Few-Shot Learning for Text Classification

Saeed Ahmadnia, Arash Yousefi Jordehi, Mahsa Hosseini Khasheh Heyran +3

The rise of Large Language Models (LLMs) has boosted the use of Few-Shot Learning (FSL) methods in natural language processing, achieving acceptable performance even when working w…

cs.CL2024

Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground

Adil Soubki, John Murzaku, Arash Yousefi Jordehi +4

Evaluating the theory of mind (ToM) capabilities of language models (LMs) has recently received a great deal of attention. However, many existing benchmarks rely on synthetic data,…

cs.CL2020

PGST: a Polyglot Gender Style Transfer method

Reza Khanmohammadi, Seyed Abolghasem Mirroshandel

Recent developments in Text Style Transfer have led this field to be more highlighted than ever. The task of transferring an input's style to another is accompanied by plenty of ch…