activity
20202026
most citedAnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model

7 citations · 9 across the 7 of their papers we have counts for

collaborators

8 papers

cs.SD2026

I'll Keep an Ear Out: Teaching AudioLLMs Proactive Audio Assistance

Amit Kumar Singh Yadav, Ritvik Shrivastava, Xuan Zhang +4

Audio large language models (AudioLLMs) operate reactively, responding only when queried. We introduce proactive audio assistance, where an AudioLLM monitors an audio stream and au…

cs.CV2025

PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding

Jang Hyun Cho, Andrea Madotto, Effrosyni Mavroudi +26

Vision-language models are integral to computer vision research, yet many high-performing models remain closed-source, obscuring their data, design and training recipe. The researc…

cs.LG2023★ 7 cited

AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model

Seungwhan Moon, Andrea Madotto, Zhaojiang Lin +10

We present Any-Modality Augmented Language Model (AnyMAL), a unified model that reasons over diverse input modality signals (i.e. text, image, video, audio, IMU motion sensor), and…

cs.CL2023★ 1 cited

Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite

Xiao Yang, Ahmed K. Mohamed, Shashank Jain +6

Label error is a ubiquitous problem in annotated data. Large amounts of label error substantially degrades the quality of deep learning models. Existing methods to tackle the label…

cs.CL2023★ 1 cited

Text Generation with Speech Synthesis for ASR Data Augmentation

Zhuangqun Huang, Gil Keren, Ziran Jiang +11

Aiming at reducing the reliance on expensive human annotations, data synthesis for Automatic Speech Recognition (ASR) has remained an active area of research. While prior work main…

cs.IR2022

A Study on the Efficiency and Generalization of Light Hybrid Retrievers

Man Luo, Shashank Jain, Anchit Gupta +6

Hybrid retrievers can take advantage of both sparse and dense retrievers. Previous hybrid retrievers leverage indexing-heavy dense retrievers. In this work, we study "Is it possibl…

cs.LG2020

Audience Creation for Consumables -- Simple and Scalable Precision Merchandising for a Growing Marketplace

Shreyas S, Harsh Maheshwari, Avijit Saha +6

Consumable categories, such as grocery and fast-moving consumer goods, are quintessential to the growth of e-commerce marketplaces in developing countries. In this work, we present…

cs.CL2020

Best Practices for Data-Efficient Modeling in NLG:How to Train Production-Ready Neural Models with Less Data

Ankit Arun, Soumya Batra, Vikas Bhardwaj +9

Natural language generation (NLG) is a critical component in conversational systems, owing to its role of formulating a correct and natural text response. Traditionally, NLG compon…