1 citations · 1 across the 16 of their papers we have counts for
18 papers
Listen, Reason, and Segment: Aligning LALMs with Editorial Judgment for Media Chapterization
Tony Alex, Wish Suharitdamrong, Sara Atito +5
Large Audio Language Models (LALMs) have made rapid progress on standardized benchmarks, yet their deployment in practical media workflows, curation, archival indexing, and content…
EquiSteer: Cross-Attention Steering Towards a Fairer Text-Guided Image Generation
Tatiana Gaintseva, Akshit Achara, Gregory Slabaugh +2
Text-to-image diffusion models power everyday creative tasks, but they still reproduce the demographic biases in their training data. On common prompts such as ``a photo of a nurse…
MidSteer: Optimal Affine Framework for Steering Generative Models
Tatiana Gaintseva, Andrew Stepanov, Ziquan Liu +4
Steering intermediate representations has emerged as a powerful strategy for controlling generative models, particularly in post-deployment alignment and safety settings. However,…
Do You See What I Am Pointing At? Gesture-Based Egocentric Video Question Answering
Yura Choi, Roy Miles, Rolandos Alexandros Potamias +3
Understanding and answering questions based on a user's pointing gesture is essential for next-generation egocentric AI assistants. However, current Multimodal Large Language Model…
DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces
Mohammad Sadil Khan, Muhammad Usama, Rolandos Alexandros Potamias +4
Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets with explicit d…
Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
Roy Miles, Aysim Toker, Andreea-Maria Oncescu +3
Reasoning with large language models often benefits from generating multiple chains-of-thought, but existing aggregation strategies are typically trajectory-level (e.g., selecting…
SATGround: A Spatially-Aware Approach for Visual Grounding in Remote Sensing
Aysim Toker, Andreea-Maria Oncescu, Roy Miles +2
Vision-language models (VLMs) are emerging as powerful generalist tools for remote sensing, capable of integrating information across diverse tasks and enabling flexible, instructi…
RetouchLLM: Training-free Code-based Image Retouching with Vision Language Models
Moon Ye-Bin, Roy Miles, Tae-Hyun Oh +2
Image retouching not only enhances visual quality but also serves as a means of expressing personal preferences and emotions. However, existing learning-based approaches require la…
Region-based Cluster Discrimination for Visual Representation Learning
Yin Xie, Kaicheng Yang, Xiang An +9
Learning visual representations is foundational for a broad spectrum of downstream tasks. Although recent vision-language contrastive models, such as CLIP and SigLIP, have achieved…
CASteer: Cross-Attention Steering for Controllable Concept Erasure
Tatiana Gaintseva, Andreea-Maria Oncescu, Chengcheng Ma +5
Diffusion models have transformed image generation, yet controlling their outputs to reliably erase undesired concepts remains challenging. Existing approaches usually require task…
"Principal Components" Enable A New Language of Images
Xin Wen, Bingchen Zhao, Ismail Elezi +2
We introduce a novel visual tokenization framework that embeds a provable PCA-like structure into the latent token space. While existing visual tokenizers primarily optimize for re…
From Attention to Activation: Unravelling the Enigmas of Large Language Models
Prannay Kaul, Chengcheng Ma, Ismail Elezi +1
We study two strange phenomena in auto-regressive Transformers: (1) the dominance of the first token in attention heads; (2) the occurrence of large outlier activations in the hidd…
Fractal Calibration for long-tailed object detection
Konstantinos Panagiotis Alexandridis, Ismail Elezi, Jiankang Deng +2
Real-world datasets follow an imbalanced distribution, which poses significant challenges in rare-category object detection. Recent studies tackle this problem by developing re-wei…
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
Roy Miles, Pradyumna Reddy, Ismail Elezi +1
Large language models (LLMs) have recently emerged as powerful tools for tackling many language-processing tasks. Despite their success, training and fine-tuning these models is st…
G3DR: Generative 3D Reconstruction in ImageNet
Pradyumna Reddy, Ismail Elezi, Jiankang Deng
We introduce a novel 3D generative method, Generative 3D Reconstruction (G3DR) in ImageNet, capable of generating diverse and high-quality 3D objects from single images, addressing…
Deep Active Learning: A Reality Check
Edrina Gashi, Jiankang Deng, Ismail Elezi
We conduct a comprehensive evaluation of state-of-the-art deep active learning methods. Surprisingly, under general settings, no single-model method decisively outperforms entropy-…
Improving Knowledge Distillation using Orthogonal Projections
Roy Miles, Ismail Elezi, Jiankang Deng
Knowledge distillation is an effective method for training small and efficient deep learning models. However, the efficacy of a single method can degenerate when transferring to ot…
Three Heads Are Better Than One: Complementary Experts for Long-Tailed Semi-supervised Learning
Chengcheng Ma, Ismail Elezi, Jiankang Deng +2
We address the challenging problem of Long-Tailed Semi-Supervised Learning (LTSSL) where labeled data exhibit imbalanced class distribution and unlabeled data follow an unknown dis…