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20212026
most citedUnderstanding the computational demands underlying visual reasoning

13 citations · 20 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Symbolic Grounding Reveals Representational Bottlenecks in Abstract Visual Reasoning

Mohit Vaishnav, Tanel Tammet

Vision--language models (VLMs) often fail on abstract visual reasoning benchmarks such as Bongard problems, raising the question of whether the main bottleneck lies in reasoning or…

cs.CV2025

Beyond the Linear Separability Ceiling: Aligning Representations in VLMs

Enrico Vompa, Tanel Tammet, Mohit Vaishnav

A challenge in advancing Visual-Language Models (VLMs) is determining whether their failures on abstract reasoning tasks, such as Bongard problems, stem from flawed perception or f…

cs.CV2025

A Cognitive Paradigm Approach to Probe the Perception-Reasoning Interface in VLMs

Mohit Vaishnav, Tanel Tammet

A fundamental challenge in artificial intelligence involves understanding the cognitive mechanisms underlying visual reasoning in sophisticated models like Vision-Language Models (…

cs.AI2023

PhD Thesis: Exploring the role of (self-)attention in cognitive and computer vision architecture

Mohit Vaishnav

We investigate the role of attention and memory in complex reasoning tasks. We analyze Transformer-based self-attention as a model and extend it with memory. By studying a syntheti…

cs.CV2022★ 2 cited

Conviformers: Convolutionally guided Vision Transformer

Mohit Vaishnav, Thomas Fel, Ivań Felipe Rodríguez +1

Vision transformers are nowadays the de-facto choice for image classification tasks. There are two broad categories of classification tasks, fine-grained and coarse-grained. In fin…

cs.CV2022★ 1 cited

A Benchmark for Compositional Visual Reasoning

Aimen Zerroug, Mohit Vaishnav, Julien Colin +2

A fundamental component of human vision is our ability to parse complex visual scenes and judge the relations between their constituent objects. AI benchmarks for visual reasoning…

cs.AI2022★ 4 cited

GAMR: A Guided Attention Model for (visual) Reasoning

Mohit Vaishnav, Thomas Serre

Humans continue to outperform modern AI systems in their ability to flexibly parse and understand complex visual scenes. Here, we present a novel module for visual reasoning, the G…

cs.CV2021★ 13 cited

Understanding the computational demands underlying visual reasoning

Mohit Vaishnav, Remi Cadene, Andrea Alamia +3

Visual understanding requires comprehending complex visual relations between objects within a scene. Here, we seek to characterize the computational demands for abstract visual rea…