From the 2 of 8 linked papers with an AI index.
8 papers
Fine-Grained Food Image Understanding via Target-Aware Data Alignment
Jui-Feng Chi, Wei-Lun Chu, Bruce Coburn +2
The paper introduces a data-centric approach that selects and refines web-collected image‑caption pairs to better train CLIP‑style vision‑language models for fine‑grained food reco…
Inference-Time Mitigation of Adversarial Political Bias in Large Language Models
Tejaswi V. Panchagnula, Bruce Coburn, Bryce J. Dietrich +3
As Large Language Models (LLMs) become the mainstay for information retrieval and summarization tasks, ensuring that they are always non-partisan and invulnerable to political bias…
Open-KNEAD: Knowledge-grounded Nutrition Estimation via Agentic Decomposition
Bruce Coburn, Jingbo Yue, Jinge Ma +3
The paper presents Open-KNEAD, a training-free, locally run agentic system that breaks down meal images into individual food items, grounds each to a nutrition database, and improv…
Not Your Stereo-Typical Estimator: Combining Vision and Language for Volume Perception
Gautham Vinod, Bruce Coburn, Siddeshwar Raghavan +1
Accurate volume estimation of objects from visual data is a long-standing challenge in computer vision with significant applications in robotics, logistics, and smart health. Exist…
DietDelta: A Vision-Language Approach for Dietary Assessment via Before-and-After Images
Gautham Vinod, Siddeshwar Raghavan, Bruce Coburn +1
Accurate dietary assessment is critical for precision nutrition, yet most image-based methods rely on a single pre-consumption image and provide only coarse, meal-level estimates.…
Can You Hear, Localize, and Segment Continually? An Exemplar-Free Continual Learning Benchmark for Audio-Visual Segmentation
Siddeshwar Raghavan, Gautham Vinod, Bruce Coburn +1
Audio-Visual Segmentation (AVS) aims to produce pixel-level masks of sound producing objects in videos, by jointly learning from audio and visual signals. However, real-world envir…