Efficient Computing

ScaleOT: Privacy-utility-scalable Offsite-tuning with Dynamic LayerReplace and Selective Rank Compression AAAI 2025 Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems EMNLP 2025 Scaling FP8 training to trillion-token LLMs ICLR 2025 Scaling Inference-Efficient Language Models ICML 2025 Scaling Laws and Efficient Inference for Ternary Language Models ACL 2025 Scaling Laws for Floating–Point Quantization Training ICML 2025 Scaling Laws for Precision ICLR 2025 Scaling Laws for Upcycling Mixture-of-Experts Language Models ICML 2025 Scaling Multi-Document Event Summarization: Evaluating Compression vs. Full-Text Approaches NAACL 2025 Scaling Probabilistic Circuits via Monarch Matrices ICML 2025 SCBench: A KV Cache-Centric Analysis of Long-Context Methods ICLR 2025 SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields ICML 2025 Schwarz–Schur Involution: Lightspeed Differentiable Sparse Linear Solvers ICML 2025 SciBERT Meets Contrastive Learning: A Solution for Scientific Hallucination Detection ACL 2025 SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation ACL 2025 SCV: Light and Effective Multi-Vector Retrieval with Sequence Compressive Vectors COLING 2025 SEARA: An Automated Approach for Obtaining Optimal Retrievers EMNLP 2025 SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding ICML 2025 Secure On-Device Video OOD Detection Without Backpropagation ICCV 2025 Seeing More, Saying More: Lightweight Language Experts are Dynamic Video Token Compressors EMNLP 2025 Seeing More with Less: Human-like Representations in Vision Models CVPR 2025 Seeing What Matters: Empowering CLIP with Patch Generation-to-Selection CVPR 2025 Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation CVPR 2025 Selective Visual Prompting in Vision Mamba AAAI 2025 Select-then-Route : Taxonomy guided Routing for LLMs EMNLP 2025