12 citations · 15 across the 10 of their papers we have counts for
13 papers
MultiPartyTurnBench: Benchmarking Floor Control in Multi-Party Spoken Dialogue
Puneet Mathur, Dinesh Manocha
Full-duplex speech systems must decide when to enter, hold, or relinquish the conversational floor, even as multiple speakers overlap or backchannel without taking it. Existing eva…
APEX-Voice: Can Voice Agents Complete Professional Workflows Through Full-Duplex Interaction
Puneet Mathur, Dinesh Manocha
Full-duplex voice agents can now listen, speak, use tools, and act during spoken interactions, but fluent dialogue does not guarantee correct completion of delegated professional w…
FD-VAD: Semantic Endpoint Detection for Streaming Full-Duplex Speech
Puneet Mathur, Dinesh Manocha
Natural turn-taking in full-duplex voice interaction requires determining from partial speech whether a pause reflects hesitation or a completed conversational intent. Acoustic voi…
DuplexSpeechBench-IFEval: Evaluating Implicit Instruction Following in Full-Duplex Voice Agents
Puneet Mathur, Dinesh Manocha
Full-duplex voice agents must continuously decide when to speak, listen, backchannel, interrupt, overlap, and yield the conversational floor. Existing benchmarks evaluate these beh…
Omni2LoRA: Coherence-Preserving Parametric Memory for Efficient Omni Language Models
Puneet Mathur, Manan Suri, Dinesh Manocha
Omnimodal language models (OLMs) enable unified audio-visual understanding, but processing long joint token sequences makes inference computationally prohibitive. While recent toke…
DocEdit-v2: Document Structure Editing Via Multimodal LLM Grounding
Manan Suri, Puneet Mathur, Franck Dernoncourt +5
Document structure editing involves manipulating localized textual, visual, and layout components in document images based on the user's requests. Past works have shown that multim…
DocSynthv2: A Practical Autoregressive Modeling for Document Generation
Sanket Biswas, Rajiv Jain, Vlad I. Morariu +5
While the generation of document layouts has been extensively explored, comprehensive document generation encompassing both layout and content presents a more complex challenge. Th…
Estimating Emotion Contagion on Social Media via Localized Diffusion in Dynamic Graphs
Trisha Mittal, Puneet Mathur, Rohan Chandra +5
We present a computational approach for estimating emotion contagion on social media networks. Built on a foundation of psychology literature, our approach estimates the degree to…
3MASSIV: Multilingual, Multimodal and Multi-Aspect dataset of Social Media Short Videos
Vikram Gupta, Trisha Mittal, Puneet Mathur +5
We present 3MASSIV, a multilingual, multimodal and multi-aspect, expertly-annotated dataset of diverse short videos extracted from short-video social media platform - Moj. 3MASSIV…
Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality
Trisha Mittal, Puneet Mathur, Aniket Bera +1
We present Affect2MM, a learning method for time-series emotion prediction for multimedia content. Our goal is to automatically capture the varying emotions depicted by characters…
Dynamic Graph Modeling of Simultaneous EEG and Eye-tracking Data for Reading Task Identification
Puneet Mathur, Trisha Mittal, Dinesh Manocha
We present a new approach, that we call AdaGTCN, for identifying human reader intent from Electroencephalogram~(EEG) and Eye movement~(EM) data in order to help differentiate betwe…
An Iterative Approach for Identifying Complaint Based Tweets in Social Media Platforms
Gyanesh Anand, Akash Gautam, Puneet Mathur +3
Twitter is a social media platform where users express opinions over a variety of issues. Posts offering grievances or complaints can be utilized by private/ public organizations t…
#MeTooMA: Multi-Aspect Annotations of Tweets Related to the MeToo Movement
Akash Gautam, Puneet Mathur, Rakesh Gosangi +3
In this paper, we present a dataset containing 9,973 tweets related to the MeToo movement that were manually annotated for five different linguistic aspects: relevance, stance, hat…