3 papers
cs.LG2026
Latent Recurrent Transformer: Architecture Exploration, Training Strategies, and Scaling Behavior
Zeyi Huang, Xuehai He, LiLiang Ren +8
We study Latent Recurrent Transformer (LRT), a lightweight augmentation of autoregressive transformers that reuses a high-level source-layer hidden state from the previous token as…
cs.IR2026
Your Embedding Model is SMARTer Than You Think
Jianrui Zhang, Hyun Jung Lee, Sukanta Ganguly +3
Multimodal retrieval relies heavily on single-vector retrievers, which compress rich, sequential token sequences into one single global representation. While efficient, they discar…
cs.CV2025
Talk in Pieces, See in Whole: Disentangling and Hierarchical Aggregating Representations for Language-based Object Detection
Sojung An, Kwanyong Park, Yong Jae Lee +1
While vision-language models (VLMs) have made significant progress in multimodal perception (e.g., open-vocabulary object detection) with simple language queries, state-of-the-art…