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cs.CV2025
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…
cs.AI2025
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…
cs.CV2025
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…