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20232026
most citedMetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation

2 citations · 2 across the 7 of their papers we have counts for

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cs.CL2026

Beyond Sequence Order: Syntax-Informed Positional Embeddings for Transformers

Haris Riaz, Hyungji Kim, Mihai Surdeanu

Positional embeddings (PE) in Transformers encode token distance and order but are largely agnostic to \textit{syntactic structure}. We introduce \textbf{S}yntax-\textbf{i}nformed…

cs.CL2026

Dr. DocBench: A Comprehensive Benchmark for Expert-Level and Difficult Document Parsing

Minglai Yang, Xinyan Velocity Yu, Pengyuan Li +22

Document parsing and recognition are fundamental capabilities for vision-language models (VLMs) and document processing systems. However, existing Optical Character Recognition (OC…

cs.CL2025★ 2 cited

MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation

Haris Riaz, Sourav Bhabesh, Vinayak Arannil +2

Recent smaller language models such Phi-3.5 and Phi-4 rely on synthetic data generated using larger Language models. Questions remain about leveraging synthetic data for other use…

cs.CL2025

Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation

Haris Riaz, Ellen Riloff, Mihai Surdeanu

We propose a simple, unsupervised method that injects pragmatic principles in retrieval-augmented generation (RAG) frameworks such as Dense Passage Retrieval to enhance the utility…

cs.CL2024

ELLEN: Extremely Lightly Supervised Learning For Efficient Named Entity Recognition

Haris Riaz, Razvan-Gabriel Dumitru, Mihai Surdeanu

In this work, we revisit the problem of semi-supervised named entity recognition (NER) focusing on extremely light supervision, consisting of a lexicon containing only 10 examples…

cs.CL2024

Best of Both Worlds: A Pliable and Generalizable Neuro-Symbolic Approach for Relation Classification

Robert Vacareanu, Fahmida Alam, Md Asiful Islam +2

This paper introduces a novel neuro-symbolic architecture for relation classification (RC) that combines rule-based methods with contemporary deep learning techniques. This approac…

cs.CL2023

Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference

Sushma Anand Akoju, Robert Vacareanu, Haris Riaz +2

We introduce a synthetic dataset called Sentences Involving Complex Compositional Knowledge (SICCK) and a novel analysis that investigates the performance of Natural Language Infer…