11 papers
Multi-modal Rail Crossing Safety Analysis
Paimon Goulart, Chansong Lim, Nícolas Roque dos Santos +4
Given one or more images of a railway crossing, can we leverage visual cues that allow us to robustly estimate how safe it is? Can we improve our ability to do so by introducing st…
Are LLM Uncertainty and Correctness Encoded by the Same Features? A Functional Dissociation via Sparse Autoencoders
Het Patel, Tiejin Chen, Hua Wei +2
Large language models can be uncertain yet correct, or confident yet wrong, raising the question of whether their output-level uncertainty and their actual correctness are driven b…
Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition
Tiejin Chen, Huaiyuan Yao, Jia Chen +2
While Large Language Model-based Multi-Agent Systems (MAS) consistently outperform single-agent systems on complex tasks, their intricate interactions introduce critical reliabilit…
Extracting and Analyzing Rail Crossing Behavior Signatures from Videos using Tensor Methods
Dawon Ahn, Het Patel, Aemal Khattak +2
Railway crossings present complex safety challenges where driver behavior varies by location, time, and conditions. Traditional approaches analyze crossings individually, limiting…
Transforming Behavioral Neuroscience Discovery with In-Context Learning and AI-Enhanced Tensor Methods
Paimon Goulart, Jordan Steinhauser, Dawon Ahn +4
Scientific discovery pipelines typically involve complex, rigid, and time-consuming processes, from data preparation to analyzing and interpreting findings. Recent advances in AI h…
A Real-Time System to Populate FRA Form 57 from News
Chansong Lim, Haz Sameen Shahgir, Yue Dong +2
Local railway committees need timely situational awareness after highway-rail grade crossing incidents, yet official Federal Railroad Administration (FRA) investigations can take d…
Preliminary Use of Vision Language Model Driven Extraction of Mouse Behavior Towards Understanding Fear Expression
Paimon Goulart, Jordan Steinhauser, Kylene Shuler +3
Integration of diverse data will be a pivotal step towards improving scientific explorations in many disciplines. This work establishes a vision-language model (VLM) that encodes v…
Robust Vision-Language Models via Tensor Decomposition: A Defense Against Adversarial Attacks
Het Patel, Muzammil Allie, Qian Zhang +2
Vision language models (VLMs) excel in multimodal understanding but are prone to adversarial attacks. Existing defenses often demand costly retraining or significant architecture c…
ExpertGenQA: Open-ended QA generation in Specialized Domains
Haz Sameen Shahgir, Chansong Lim, Jia Chen +2
Generating high-quality question-answer pairs for specialized technical domains remains challenging, with existing approaches facing a tradeoff between leveraging expert examples a…
Automating Data Science Pipelines with Tensor Completion
Shaan Pakala, Bryce Graw, Dawon Ahn +5
Hyperparameter optimization is an essential component in many data science pipelines and typically entails exhaustive time and resource-consuming computations in order to explore t…
Towards Aligned Canonical Correlation Analysis: Preliminary Formulation and Proof-of-Concept Results
Biqian Cheng, Evangelos E. Papalexakis, Jia Chen
Canonical Correlation Analysis (CCA) has been widely applied to jointly embed multiple views of data in a maximally correlated latent space. However, the alignment between various…