1 citations · 4 across the 17 of their papers we have counts for
18 papers
Spatial Reasoning via Modality Switching Between Language and Symbolic Representations
Shreya Rajpal, Tanawan Premsri, Parisa Kordjamshidi
Human reasoning is inherently multimodal: when problems become difficult, we rarely think in words alone. We often externalize our reasoning by sketching diagrams or drawing grids…
SATURN: Symbolic Spatial Reasoning for Multi-Perspective Grounding
Danial Kamali, Tanawan Premsri, Shreya Rajpal +3
Vision-Language Models (VLMs) remain unreliable when spatial reasoning requires composing relations whose meanings depend on frames of reference. Existing tool-augmented spatial re…
Reasoners or Translators? Contamination-aware Evaluation and Neuro-Symbolic Robustness in Tax Law
Parisa Kordjamshidi, Samer Aslan, Madhavan Seshadri +2
Recent advances in large language models (LLMs) have significantly enhanced automated legal reasoning. Yet, it remains unclear whether their performance reflects genuine legal reas…
Discovering Failure Modes in Vision-Language Models using RL
Kanishk Jain, Qian Yang, Shravan Nayak +3
Vision-language Models (VLMs), despite achieving strong performance on multimodal benchmarks, often misinterpret straightforward visual concepts that humans identify effortlessly,…
An Agentic Framework for Neuro-Symbolic Programming
Aliakbar Nafar, Chetan Chigurupati, Danial Kamali +2
Integrating symbolic constraints into deep learning models could make them more robust, interpretable, and data-efficient. Still, it remains a time-consuming and challenging task.…
Referring Expressions as a Lens into Spatial Language Grounding in Vision-Language Models
Akshar Tumu, Varad Shinde, Parisa Kordjamshidi
Spatial Reasoning is an important component of human cognition and is an area in which the latest Vision-language models (VLMs) show signs of difficulty. The current analysis works…
NePTune: A Neuro-Pythonic Framework for Tunable Compositional Reasoning on Vision-Language
Danial Kamali, Parisa Kordjamshidi
Modern Vision-Language Models (VLMs) have achieved impressive performance in various tasks, yet they often struggle with compositional reasoning, the ability to decompose and recom…
Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis
Sania Sinha, Tanawan Premsri, Danial Kamali +1
Neurosymbolic (NeSy) frameworks combine neural representations and learning with symbolic representations and reasoning. Combining the reasoning capacities, explainability, and int…
FoR-SALE: Frame of Reference-guided Spatial Adjustment in LLM-based Diffusion Editing
Tanawan Premsri, Parisa Kordjamshidi
Current text-to-image generation models, even state-of-the-art models, exhibit a significant performance gap when spatial expressions are described from non-camera perspectives. To…
Exploring Spatial Language Grounding Through Referring Expressions
Akshar Tumu, Parisa Kordjamshidi
Spatial Reasoning is an important component of human cognition and is an area in which the latest Vision-language models (VLMs) show signs of difficulty. The current analysis works…
FoREST: Frame of Reference Evaluation in Spatial Reasoning Tasks
Tanawan Premsri, Parisa Kordjamshidi
Spatial reasoning is a fundamental aspect of human intelligence. One key concept in spatial cognition is the Frame of Reference, which identifies the perspective of spatial express…
NeSyCoCo: A Neuro-Symbolic Concept Composer for Compositional Generalization
Danial Kamali, Elham J. Barezi, Parisa Kordjamshidi
Compositional generalization is crucial for artificial intelligence agents to solve complex vision-language reasoning tasks. Neuro-symbolic approaches have demonstrated promise in…
Disentangling Knowledge-based and Visual Reasoning by Question Decomposition in KB-VQA
Elham J. Barezi, Parisa Kordjamshidi
We study the Knowledge-Based visual question-answering problem, for which given a question, the models need to ground it into the visual modality to find the answer. Although many…
Neuro-symbolic Training for Reasoning over Spatial Language
Tanawan Premsri, Parisa Kordjamshidi
Spatial reasoning based on natural language expressions is essential for everyday human tasks. This reasoning ability is also crucial for machines to interact with their environmen…
A Survey on Compositional Learning of AI Models: Theoretical and Experimental Practices
Sania Sinha, Tanawan Premsri, Parisa Kordjamshidi
Compositional learning, mastering the ability to combine basic concepts and construct more intricate ones, is crucial for human cognition, especially in human language comprehensio…
Find The Gap: Knowledge Base Reasoning For Visual Question Answering
Elham J. Barezi, Parisa Kordjamshidi
We analyze knowledge-based visual question answering, for which given a question, the models need to ground it into the visual modality and retrieve the relevant knowledge from a g…
Syntax-Guided Transformers: Elevating Compositional Generalization and Grounding in Multimodal Environments
Danial Kamali, Parisa Kordjamshidi
Compositional generalization, the ability of intelligent models to extrapolate understanding of components to novel compositions, is a fundamental yet challenging facet in AI resea…
Using Persuasive Writing Strategies to Explain and Detect Health Misinformation
Danial Kamali, Joseph Romain, Huiyi Liu +3
Nowadays, the spread of misinformation is a prominent problem in society. Our research focuses on aiding the automatic identification of misinformation by analyzing the persuasive…