activity
20222026
most citedTowards Neuro-Symbolic Video Understanding

9 citations · 13 across the 16 of their papers we have counts for

collaborators

17 papers

cs.MA2026

Bayesian Partner Modelling enables Adaptive Replanning for LLM Coordination

Harsh Goel, Aditya Sai Ellendula, Vaishnav Tadiparthi +3

Multi-agent Large Language Model (LLM) systems often struggle to collaborate with new teammates whose strategies shift mid-task. Because agents execute multi-step or temporally ext…

cs.CV2026

CrossView: Can Vision-Language Models Reason Across Cameras?

Sahil Shah, S P Sharan, Harsh Goel +4

Video understanding benchmarks have long centered on single-camera settings, where modern multi-modal language models achieve strong performance across image and video tasks. Yet,…

cs.CV2026

Incentivizing Vision Language Models to Search for Long Video Question Answering

Harsh Goel, S P Sharan, Sahil Shah +4

We introduce VSeek, an agentic framework that transforms long-video question answering (LVQA) from a passive, single-pass perception task into a multi-turn retrieval process. VSeek…

cs.LG2026

-R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data

Harsh Goel, Akhil Udathu, Susmija Jabbireddy +2

Reinforcement learning (RL) post-training has enabled newer capabilities in models, such as agentic tool-use for search. However, these models struggle primarily due to limitations…

cs.LG2026

CoordLight: Learning Decentralized Coordination for Network-Wide Traffic Signal Control

Yifeng Zhang, Harsh Goel, Peizhuo Li +3

Adaptive traffic signal control (ATSC) is crucial in alleviating congestion, maximizing throughput and promoting sustainable mobility in ever-expanding cities. Multi-Agent Reinforc…

cs.CV2026

SSR: A Generic Framework for Text-Aided Map Compression for Localization

Mohammad Omama, Po-han Li, Harsh Goel +6

Mapping is crucial in robotics for localization and downstream decision-making. As robots are deployed in ever-broader settings, the maps they rely on continue to increase in size.…

cs.CV2026

RT-NeuS: Towards Real-Time Neuro-Symbolic Video Understanding via Adaptive Temporal Verification

Shawn Liang, Sahil Shah, Chengwei Zhou +5

Long-form video question answering (LVQA) requires answering natural-language queries about videos spanning minutes to hours, demanding temporal reasoning across thousands of frame…

cs.CV2025

ObjectAlign: Neuro-Symbolic Object Consistency Verification and Correction

Mustafa Munir, Harsh Goel, Xiwen Wei +6

Video editing and synthesis often introduce object inconsistencies, such as frame flicker and identity drift that degrade perceptual quality. To address these issues, we introduce…

cs.CV2025

NeuS-QA: Grounding Long-Form Video Understanding in Temporal Logic and Neuro-Symbolic Reasoning

Sahil Shah, S P Sharan, Harsh Goel +5

While vision-language models (VLMs) excel at tasks involving single images or short videos, they still struggle with Long Video Question Answering (LVQA) due to its demand for comp…

cs.AI2025

A Challenge to Build Neuro-Symbolic Video Agents

Sahil Shah, Harsh Goel, Sai Shankar Narasimhan +4

Modern video understanding systems excel at tasks such as scene classification, object detection, and short video retrieval. However, as video analysis becomes increasingly central…

cs.MA2025★ 1 cited

R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning

Harsh Goel, Mohammad Omama, Behdad Chalaki +3

Multi-agent reinforcement learning (MARL) has achieved significant progress in large-scale traffic control, autonomous vehicles, and robotics. Drawing inspiration from biological s…

cs.CV2025

We'll Fix it in Post: Improving Text-to-Video Generation with Neuro-Symbolic Feedback

Minkyu Choi, S P Sharan, Harsh Goel +2

Current text-to-video (T2V) generation models are increasingly popular due to their ability to produce coherent videos from textual prompts. However, these models often struggle to…

cs.CV2024★ 1 cited

SynDiff-AD: Improving Semantic Segmentation and End-to-End Autonomous Driving with Synthetic Data from Latent Diffusion Models

Harsh Goel, Sai Shankar Narasimhan, Oguzhan Akcin +1

In recent years, significant progress has been made in collecting large-scale datasets to improve segmentation and autonomous driving models. These large-scale datasets are often d…

cs.CV2024

Neuro-Symbolic Evaluation of Text-to-Video Models using Formal Verification

S P Sharan, Minkyu Choi, Sahil Shah +3

Recent advancements in text-to-video models such as Sora, Gen-3, MovieGen, and CogVideoX are pushing the boundaries of synthetic video generation, with adoption seen in fields like…

cs.CV2024★ 9 cited

Towards Neuro-Symbolic Video Understanding

Minkyu Choi, Harsh Goel, Mohammad Omama +3

The unprecedented surge in video data production in recent years necessitates efficient tools to extract meaningful frames from videos for downstream tasks. Long-term temporal reas…

cs.LG2023★ 1 cited

SocialLight: Distributed Cooperation Learning towards Network-Wide Traffic Signal Control

Harsh Goel, Yifeng Zhang, Mehul Damani +1

Many recent works have turned to multi-agent reinforcement learning (MARL) for adaptive traffic signal control to optimize the travel time of vehicles over large urban networks. Ho…

cs.RO2022★ 1 cited

Reinforcement Learning for Agile Active Target Sensing with a UAV

Harsh Goel, Laura Jarin Lipschitz, Saurav Agarwal +2

Active target sensing is the task of discovering and classifying an unknown number of targets in an environment and is critical in search-and-rescue missions. This paper develops a…