Hugging Face Trending Papers
Retrieval Geometry Shapes Cache-Based Clip Adaptation
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arXiv Computer Vision
Sep 22
Retrieval Geometry Shapes Cache-Based Clip Adaptation
The paper investigates how the choice of retrieval encoder affects cache‑based test‑time adaptation for CLIP. By keeping the memory fixed and varying the retrieval space across sixteen encoders, the authors show that retrieval space can dramatically alter performance, with gains ranging from +0.44 to +19.7 points on ImageNet‑A. They introduce MARC, a training‑free system that pairs frozen CLIP with DINOv2‑B for retrieval, achieving superior out‑of‑distribution accuracy and efficiency compared to prior methods.
Hugging Face Trending Papers
Sep 22
Calibrating Retrieval Geometry: Reliability-Guided Training-Free Aggregation for Visual Place Recognition
Frozen visual foundation models provide transferable features for visual place recognition, but fixed aggregation can suppress useful distinctions in new environments. We introduce TFA, a reliability-...
arXiv Computer Vision
Sep 23
Calibrating Retrieval Geometry: Reliability-Guided Training-Free Aggregation for Visual Place Recognition
The paper introduces TFA, a training‑free aggregation technique that calibrates frozen visual foundation models for visual place recognition. TFA uses cross‑codebook agreement, retrieval coverage, and spectral statistics to adjust residual assignment, spectral shaping, and global‑feature fusion without requiring place labels or task‑specific weights. Experiments with a DINOv2‑B backbone show significant Recall@1 gains over existing training‑free methods across multiple benchmarks, demonstrating that reliability‑guided aggregation can unlock additional retrieval performance from frozen representations.
arXiv AI
Jun 2
STaR-KV: Spatio-Temporal Adaptive Re-weighting for KV Cache Compression in GUI Vision-Language Models
arXiv:2606. 01790v1 Announce Type: cross Abstract: Vision-language-model-based graphical user interface (GUI) agents have shown broad automation capabilities, yet deployment is bottlenecked by a key-value (KV) cache that grows linearly with interaction steps.
arXiv AI
Aug 14
LipCache: A Local Inference Proxy with Certified Caching for Edge Image Classification Service
arXiv:2608. 13144v1 Announce Type: cross Abstract: As edge-side vision services continue to expand toward low-latency, high-throughput scenarios, reducing the inference cost of vision models without sacrificing reliability has become a central concern.
arXiv Computer Vision
3d ago
Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution
arXiv:2605.25333v3 Announce Type: replace Abstract: Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption...