activity
20242026
collaborators

13 papers

cs.AI2026

Spatial Reasoning via Modality Switching Between Language and Symbolic Representation

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…

cs.CV2026

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 neuro-symbolic methods ma…

cs.AI2026

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…

cs.CV2026

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,…

cs.AI2026

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.…

cs.CL2025

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…