Posters

SPRINQL: Sub-optimal Demonstrations for Offline Imitation Learning

SPO: A novel model-based RL algorithm leverages parallelisable Monte Carlo tree search for efficient and robust policy improvement in both discrete and continuous environments.

SplitNeRF: One-hour training on a single GPU yields state-of-the-art scene geometry, lighting, and material property estimation!

Researchers introduce Video Gaussian Representation (VGR) for versatile video processing, embedding videos into explicit 3D Gaussians for intuitive motion and appearance modeling.

Spiking Experts Mixture Mechanism (SEMM) boosts Spiking Transformers by integrating Mixture-of-Experts for efficient, sparse conditional computation, achieving significant performance improvements on …

STMixer: a novel SNN architecture enabling high performance on both synchronous and asynchronous neuromorphic hardware, achieving comparable results to spiking transformers with drastically lower powe…

SpikeSlicer: An adaptive event stream slicer using a spiking neural network (SNN) to efficiently split events for improved downstream processing in object tracking and recognition.

Spiking Graph Neural Networks (SGNNs) on Riemannian Manifolds achieve superior performance and energy efficiency via a novel Manifold Spiking GNN (MSG).

SpikedAttention: Training-free transformer-to-SNN conversion achieving state-of-the-art accuracy and 42% energy reduction!

Energy-efficient neuromorphic SSL model achieves state-of-the-art accuracy and robustness using Resonate-and-Fire neurons and a novel multi-auditory attention module.

SFCNet, a novel spherical frustum sparse convolution network, tackles LiDAR point cloud semantic segmentation by eliminating quantized information loss, leading to superior performance, especially for…

SpGesture: A source-free domain-adaptive SEMG gesture recognition system using a novel Spiking Jaccard Attentive Neural Network achieves real-time performance with high accuracy.

SpelsNet, a novel neural architecture, achieves accurate 3D point cloud segmentation into surface primitives by incorporating B-Rep graph structure supervision, leading to topologically consistent res…

SpeedLoader: A groundbreaking I/O efficient scheme dramatically boosts LLM training & inference speed on diverse hardware, even with limited resources!

SpeechForensics leverages audio-visual speech representation learning to achieve superior face forgery detection, outperforming state-of-the-art methods in cross-dataset generalization and robustness.

SpeechAlign: Iteratively aligning speech generation models to human preferences via preference optimization, bridging distribution gaps for improved speech quality.

Speculative MCTS accelerates AlphaZero training by implementing speculative execution, enabling parallel processing of future moves and reducing latency by up to 5.8x.

Boosting LLM inference speed, a CTC-based draft model significantly improves speculative decoding’s acceptance rate, leading to faster inference.

SRCPO: a novel spectral risk measure-constrained RL algorithm guaranteeing convergence to a global optimum, outperforming existing methods in continuous control tasks.

PGLDM, a novel algorithm, accurately identifies shared and private dynamics in two generalized-linear time series, improving model accuracy and enabling lower-dimensional latent state representations.