activity
20172024
most citedNeural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding

349 citations · 463 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

Compositional Physical Reasoning of Objects and Events from Videos

Zhenfang Chen, Shilong Dong, Kexin Yi +5

Understanding and reasoning about objects' physical properties in the natural world is a fundamental challenge in artificial intelligence. While some properties like colors and sha…

cs.AI2024★ 1 cited

M3GIA: A Cognition Inspired Multilingual and Multimodal General Intelligence Ability Benchmark

Wei Song, Yadong Li, Jianhua Xu +8

As recent multi-modality large language models (MLLMs) have shown formidable proficiency on various complex tasks, there has been increasing attention on debating whether these mod…

cs.CV2022★ 14 cited

ComPhy: Compositional Physical Reasoning of Objects and Events from Videos

Zhenfang Chen, Kexin Yi, Yunzhu Li +4

Objects' motions in nature are governed by complex interactions and their properties. While some properties, such as shape and material, can be identified via the object's visual a…

cs.CL2022

Immersive Text Game and Personality Classification

Wanshui Li, Yifan Bai, Jiaxuan Lu +1

We designed and built a game called \textit{Immersive Text Game}, which allows the player to choose a story and a character, and interact with other characters in the story in an i…

cs.LG2020★ 22 cited

Visual Grounding of Learned Physical Models

Yunzhu Li, Toru Lin, Kexin Yi +5

Humans intuitively recognize objects' physical properties and predict their motion, even when the objects are engaged in complicated interactions. The abilities to perform physical…

cs.CV2019★ 69 cited

CLEVRER: CoLlision Events for Video REpresentation and Reasoning

Kexin Yi, Chuang Gan, Yunzhu Li +4

The ability to reason about temporal and causal events from videos lies at the core of human intelligence. Most video reasoning benchmarks, however, focus on pattern recognition fr…

cs.AI2018★ 349 cited

Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding

Kexin Yi, Jiajun Wu, Chuang Gan +3

We marry two powerful ideas: deep representation learning for visual recognition and language understanding, and symbolic program execution for reasoning. Our neural-symbolic visua…

stat.ML2017★ 8 cited

Roll-back Hamiltonian Monte Carlo

Kexin Yi, Finale Doshi-Velez

We propose a new framework for Hamiltonian Monte Carlo (HMC) on truncated probability distributions with smooth underlying density functions. Traditional HMC requires computing the…