1 citations · 1 across the 2 of their papers we have counts for
7 papers
Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
Christopher Clark, Jieyu Zhang, Zixian Ma +18
Today's strongest video-language models (VLMs) remain proprietary. The strongest open-weight models either rely on synthetic data from proprietary VLMs, effectively distilling from…
SAGE: Training Smart Any-Horizon Agents for Long Video Reasoning with Reinforcement Learning
Jitesh Jain, Jialuo Li, Zixian Ma +7
As humans, we are natural any-horizon reasoners, i.e., we can decide whether to iteratively skim long videos or watch short ones in full when necessary for a given task. With this…
AUGUSTUS: An LLM-Driven Multimodal Agent System with Contextualized User Memory
Jitesh Jain, Shubham Maheshwari, Ning Yu +2
Riding on the success of LLMs with retrieval-augmented generation (RAG), there has been a growing interest in augmenting agent systems with external memory databases. However, the…
Elevating Visual Perception in Multimodal LLMs with Visual Embedding Distillation
Jitesh Jain, Zhengyuan Yang, Humphrey Shi +2
In recent times, the standard practice for developing MLLMs is to feed features from vision encoder(s) into the LLM and train with natural language supervision. This approach often…
Person Recognition at Altitude and Range: Fusion of Face, Body Shape and Gait
Feng Liu, Nicholas Chimitt, Lanqing Guo +16
We address the problem of whole-body person recognition in unconstrained environments. This problem arises in surveillance scenarios such as those in the IARPA Biometric Recognitio…
Slow-Fast Architecture for Video Multi-Modal Large Language Models
Min Shi, Shihao Wang, Chieh-Yun Chen +6
Balancing temporal resolution and spatial detail under limited compute budget remains a key challenge for video-based multi-modal large language models (MLLMs). Existing methods ty…