activity
20202026
most citedUniversal Adversarial Perturbations: A Survey

28 citations · 28 across the 10 of their papers we have counts for

collaborators

12 papers

cs.SD2026

ATTEST: Evidence-Grounded Reinforcement Learning for Long-Audio Temporal Understanding

Ashutosh Chaubey, Jinxi Guo, Minh Tran +2

Temporal grounding is fundamental to audio understanding, yet large audio language models (LALMs) remain weak at it on long audio, where hallucinations compound and annotated data…

cs.SD2026

Do Audio LLMs Listen or Read? Analyzing and Mitigating Paralinguistic Failures with VoxParadox

Jiacheng Pang, Ashutosh Chaubey, Mohammad Soleymani

Audio large language models (Audio LLMs) demonstrate strong performance on speech understanding tasks, yet their ability to understand paralinguistic information remains limited. T…

cs.CV2026

MoD-DPO: Towards Mitigating Cross-modal Hallucinations in Omni LLMs using Modality Decoupled Preference Optimization

Ashutosh Chaubey, Jiacheng Pang, Mohammad Soleymani

Omni-modal large language models (omni LLMs) have recently achieved strong performance across audiovisual understanding tasks, yet they remain highly susceptible to cross-modal hal…

cs.CV2026

GDPO-Listener: Expressive Interactive Head Generation via Auto-Regressive Flow Matching and Group reward-Decoupled Policy Optimization

Zhangyu Jin, Maksim Siniukov, Deuksin Kwon +2

Generating realistic 3D head motion for dyadic interactions is a significant challenge in virtual human synthesis. While recent methods achieve impressive results with speaking hea…

cs.LG2026

AVERE: Improving Audiovisual Emotion Reasoning with Preference Optimization

Ashutosh Chaubey, Jiacheng Pang, Maksim Siniukov +1

Emotion understanding is essential for building socially intelligent agents. Although recent multimodal large language models have shown strong performance on this task, two key ch…

cs.CV2025

Face-LLaVA: Facial Expression and Attribute Understanding through Instruction Tuning

Ashutosh Chaubey, Xulang Guan, Mohammad Soleymani

The human face plays a central role in social communication, necessitating the use of performant computer vision tools for human-centered applications. We propose Face-LLaVA, a mul…

cs.CV2025

DiTaiListener: Controllable High Fidelity Listener Video Generation with Diffusion

Maksim Siniukov, Di Chang, Minh Tran +3

Generating naturalistic and nuanced listener motions for extended interactions remains an open problem. Existing methods often rely on low-dimensional motion codes for facial behav…

cs.CV2024

ContextIQ: A Multimodal Expert-Based Video Retrieval System for Contextual Advertising

Ashutosh Chaubey, Anoubhav Agarwaal, Sartaki Sinha Roy +2

Contextual advertising serves ads that are aligned to the content that the user is viewing. The rapid growth of video content on social platforms and streaming services, along with…

eess.AS2023

Meta-Learning Framework for End-to-End Imposter Identification in Unseen Speaker Recognition

Ashutosh Chaubey, Sparsh Sinha, Susmita Ghose

Speaker identification systems are deployed in diverse environments, often different from the lab conditions on which they are trained and tested. In this paper, first, we show the…

eess.AS2022

Improved Relation Networks for End-to-End Speaker Verification and Identification

Ashutosh Chaubey, Sparsh Sinha, Susmita Ghose

Speaker identification systems in a real-world scenario are tasked to identify a speaker amongst a set of enrolled speakers given just a few samples for each enrolled speaker. This…

cs.IR2021

OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis

Sumit Shekhar, Bhanu Prakash Reddy Guda, Ashutosh Chaubey +2

Documents are central to many business systems, and include forms, reports, contracts, invoices or purchase orders. The information in documents is typically in natural language, b…

cs.CV2020★ 28 cited

Universal Adversarial Perturbations: A Survey

Ashutosh Chaubey, Nikhil Agrawal, Kavya Barnwal +2

Over the past decade, Deep Learning has emerged as a useful and efficient tool to solve a wide variety of complex learning problems ranging from image classification to human pose…