1 citations · 1 across the 16 of their papers we have counts for
10 papers · 1 filter
Fine-Grained Multi Image Object Hallucination Benchmark
Joonki Min, Chaeyun Kim, Hyungwook Choi +4
Multimodal Large Language Models (MLLMs) are increasingly deployed in multi-image scenarios requiring complex reasoning across visual contexts. However, current MLLMs remain fundam…
Domain Generalization via Text-Anchored Information Bottleneck
Eunyi Lyou, Yunjeong Choi, Junho Lee +1
Visual recognition models often fail when deployed in new environments. Domain Generalization (DG) addresses this by learning representations that remain invariant to environment-s…
Generative Modeling of Quantum Distribution with Functional Flow Matching
Jaehoon Hahm, Tak Hur, Joonseok Lee +1
The emergence of powerful deep generative models based on diffusion and flow matching has enabled the learning and modeling of complex distributions. Learning quantum distributions…
Equivariant Latent Alignment via Flow Matching under Group Symmetries
Sunghyun Kim, Jaehoon Hahm, Jeongwoo Shin +1
Geometry-aware generative models and novel view synthesis approaches have shown strong potential in visual fidelity and consistency. In parallel, equivariant representation learnin…
EVIDENT: Routing MLLM Adaptation through Entity-Grounded Visual Evidence for Cross-Domain Video Temporal Grounding
Geo Ahn, Jiwook Han, Youngrae Kim +2
Fine-tuning MLLMs for Video Temporal Grounding (VTG) often improves in-domain performance but degrades sharply under domain shift. In this work, we find that this failure is primar…
Geometry-Aware Image Flow Matching
Junho Lee, Kwanseok Kim, Joonseok Lee
Recent advances in generative models highlight the power of geometry-aware modeling in manifold-constrained settings. Yet, for natural images, the field remains confined to Euclide…
ArtSplat: Feed-Forward Articulated 3D Gaussian Splatting from Sparse Multi-State Uncalibrated Views
Inseo Lee, Yoonji Kim, Eugene Sohn +4
Articulated object reconstruction from sparse-view images is an ill-posed problem that requires simultaneous inference of geometry and underlying articulation structure. Existing m…
A More Word-like Image Tokenization for MLLMs
Hyun Lee, Hyemin Jeong, Yejin Kim +4
Modern multimodal large language models (MLLMs) typically keep the language model fixed and train a visual projector that maps the pixels into a sequence of tokens in its embedding…
Efficient Adjoint Matching for Fine-tuning Diffusion Models
Jeongwoo Shin, Dongsoo Shin, Yuchen Zhu +5
Reward fine-tuning has become a common approach for aligning pretrained diffusion and flow models with human preferences in text-to-image generation. Among reward-gradient-based me…
Towards Motion-aware Referring Image Segmentation
Chaeyun Kim, Seunghoon Yi, Yejin Kim +2
Referring Image Segmentation (RIS) requires identifying objects from images based on textual descriptions. We observe that existing methods significantly underperform on motion-rel…