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Found 11 papers, 3 papers with code
Efficient Vision-Language Models by Summarizing Visual Tokens into Compact Registers
Victor adds a few learnable register tokens after the visual tokens and summarizes the visual information into these registers using the first few layers in the language tower of VLMs.
Apple Intelligence Foundation Language Models
We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large server-based language model designed for Private Cloud Compute.
LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference
The inference of transformer-based large language models consists of two sequential stages: 1) a prefilling stage to compute the KV cache of prompts and generate the first token, and 2) a decoding stage to generate subsequent tokens.
Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation
Despite the successes of large language models (LLMs), they exhibit significant drawbacks, particularly when processing long contexts.
Speculative Streaming: Fast LLM Inference without Auxiliary Models
Speculative decoding is a prominent technique to speed up the inference of a large target language model based on predictions of an auxiliary draft model.
FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline
Compared to existing NeRF+SR methods, our pipeline mitigates the SR computing overhead and can be trained up to 23x faster, making it feasible to run on consumer devices such as the Apple MacBook.
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large Language Models
Since Large Language Models or LLMs have demonstrated high-quality performance on many complex language tasks, there is a great interest in bringing these LLMs to mobile devices for faster responses and better privacy protection.
Deformer: Dynamic Fusion Transformer for Robust Hand Pose Estimation
Accurately estimating 3D hand pose is crucial for understanding how humans interact with the world.
Domain Adaptive Hand Keypoint and Pixel Localization in the Wild
We aim to improve the performance of regressing hand keypoints and segmenting pixel-level hand masks under new imaging conditions (e. g., outdoors) when we only have labeled images taken under very different conditions (e. g., indoors).
Sequential Voting with Relational Box Fields for Active Object Detection
While our voting function is able to improve the bounding box of the active object, one round of voting is typically not enough to accurately localize the active object.
Ego4D: Around the World in 3,000 Hours of Egocentric Video
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite.
