papers

Publications (7)

cs.CL2016

A Data-Driven Approach for Semantic Role Labeling from Induced Grammar Structures in Language

Vivek Datla, David Lin, Max Louwerse +1

Semantic roles play an important role in extracting knowledge from text. Current unsupervised approaches utilize features from grammar structures, to induce semantic roles. The dep…

cs.CL2015

Predicting the top and bottom ranks of billboard songs using Machine Learning

Vivek Datla, Abhinav Vishnu

The music industry is a $130 billion industry. Predicting whether a song catches the pulse of the audience impacts the industry. In this paper we analyze language inside the lyrics…

cs.CL2025

Confidence-Based Response Abstinence: Improving LLM Trustworthiness via Activation-Based Uncertainty Estimation

Zhiqi Huang, Vivek Datla, Chenyang Zhu +4

We propose a method for confidence estimation in retrieval-augmented generation (RAG) systems that aligns closely with the correctness of large language model (LLM) outputs. Confid…

cs.IR2020

An Ontology-driven Treatment Article Retrieval System for Precision Oncology

Zheng Chen, Sadid A. Hasan, Joey Liu +7

This paper presents an ontology-driven treatment article retrieval system developed and experimented using the data and ground truths provided by the TREC 2017 precision medicine t…

cs.CL2018

DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference

Reza Ghaeini, Sadid A. Hasan, Vivek Datla +7

We present a novel deep learning architecture to address the natural language inference (NLI) task. Existing approaches mostly rely on simple reading mechanisms for independent enc…

cs.CL2017

Condensed Memory Networks for Clinical Diagnostic Inferencing

Aaditya Prakash, Siyuan Zhao, Sadid A. Hasan +5

Diagnosis of a clinical condition is a challenging task, which often requires significant medical investigation. Previous work related to diagnostic inferencing problems mostly con…