13 papers
From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models
Lingyao Li, Runlong Yu, Qikai Hu +4
Image geolocalization, the task of identifying the geographic location depicted in an image, is important for applications in crisis response, digital forensics, and location-based…
OODBench: Out-of-Distribution Benchmark for Large Vision-Language Models
Ling Lin, Yang Bai, Heng Su +5
Existing Visual-Language Models (VLMs) have achieved significant progress by being trained on massive-scale datasets, typically under the assumption that data are independent and i…
Unrewarded Exploration in Large Language Models Reveals Latent Learning from Psychology
Jian Xiong, Jingbo Zhou, Zihan Zhou +6
Latent learning, classically theorized by Tolman, shows that biological agents (e.g., rats) can acquire internal representations of their environment without rewards, enabling rapi…
Alchemist: Unlocking Efficiency in Text-to-Image Model Training via Meta-Gradient Data Selection
Kaixin Ding, Yang Zhou, Xi Chen +5
Recent advances in Text-to-Image (T2I) generative models, such as Imagen, Stable Diffusion, and FLUX, have led to remarkable improvements in visual quality. However, their performa…
RELIC: Interactive Video World Model with Long-Horizon Memory
Yicong Hong, Yiqun Mei, Chongjian Ge +11
A truly interactive world model requires three key ingredients: real-time long-horizon streaming, consistent spatial memory, and precise user control. However, most existing approa…
Demystify Protein Generation with Hierarchical Conditional Diffusion Models
Zinan Ling, Yi Shi, Brett McKinney +3
Generating novel and functional protein sequences is critical to a wide range of applications in biology. Recent advancements in conditional diffusion models have shown impressive…