activity
20222026
most citedVisual Representations of Physiological Signals for Fake Video Detection

2 citations · 5 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR2026★ 2 cited

Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval

Sachin Yadav, Deepak Saini, Anirudh Buvanesh +6

We develop accurate and efficient solutions for large-scale retrieval tasks where novel (zero-shot) items can arrive continuously at a rapid pace. Conventional Siamese-style approa…

cs.RO2026

Do as I Do: Dexterous Manipulation Data from Everyday Human Videos

Bhawna Paliwal, Haritheja Etukuru, William Liang +3

How can we scalably generate data for robotic manipulation, especially on human-like platforms such as dexterous multi-fingered hands? Learning from human videos has recently emerg…

cs.IR2026

HORIZON: A Benchmark for In-the-wild User Behaviour Modeling

Arnav Goel, Pranjal A Chitale, Bhawna Paliwal +2

User behavior in the real world is diverse, cross-domain, and spans long time horizons. Existing user modeling benchmarks however remain narrow, focusing mainly on short sessions a…

cs.IR2024

CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks

Bhawna Paliwal, Deepak Saini, Mudit Dhawan +6

Ranking a set of items based on their relevance to a given query is a core problem in search and recommendation. Transformer-based ranking models are the state-of-the-art approache…

cs.CV2022★ 2 cited

Visual Representations of Physiological Signals for Fake Video Detection

Kalin Stefanov, Bhawna Paliwal, Abhinav Dhall

Realistic fake videos are a potential tool for spreading harmful misinformation given our increasing online presence and information intake. This paper presents a multimodal learni…

cs.LG2022★ 1 cited

NGAME: Negative Mining-aware Mini-batching for Extreme Classification

Kunal Dahiya, Nilesh Gupta, Deepak Saini +16

Extreme Classification (XC) seeks to tag data points with the most relevant subset of labels from an extremely large label set. Performing deep XC with dense, learnt representation…