Posters

BoNBON alignment optimizes large language model (LLM) outputs towards human preferences using best-of-n sampling, maximizing win-rate against base models with minimal off-target impact.

Boolean Logic Deep Learning (BOLD) revolutionizes deep learning by enabling training with Boolean weights and activations, achieving state-of-the-art accuracy with drastically reduced energy consumpti…

Diversified Block Sparse Bayesian Learning (DivSBL) improves block sparse signal recovery by adapting to unknown block structures, enhancing accuracy and robustness over existing methods.

BLoB: Bayesian Low-Rank Adaptation by Backpropagation enhances LLMs by jointly tuning mean and covariance of parameters during fine-tuning, improving uncertainty estimation and generalization.

BIRD: a novel blind image restoration method jointly optimizes degradation model parameters and the restored image, ensuring realistic outputs via fast diffusion inversion and achieving state-of-the-a…

BLAST matrix learns efficient weight structures for faster deep learning inference, achieving significant compression and performance gains on various models.

Black-Box Forgetting achieves selective forgetting in large pre-trained models by optimizing input prompts, not model parameters, thus enabling targeted class removal without requiring internal model …

BitsFusion achieves 7.9x smaller Stable Diffusion models by quantizing UNet weights to 1.99 bits, surprisingly improving image generation quality!

BitDelta drastically shrinks fine-tuned LLMs by quantizing their weight deltas to just one bit, achieving 10x memory reduction and latency improvements without sacrificing performance.

bit2bit reconstructs high-quality videos from sparse, binary quanta image sensor data using self-supervised photon location prediction, significantly improving resolution and usability.

Bisimulation metrics and optimal transport distances are equivalent and can be computed efficiently using a novel Sinkhorn Value Iteration algorithm.

BISCOPE: AI-generated text detection using a novel bidirectional method that outperforms existing techniques by leveraging both prediction and memorization of preceding tokens.

Biologically-inspired AI model integrates learning & visual guidance via a novel ‘Counter-Hebb’ learning mechanism, achieving competitive performance on multi-task learning benchmarks.

Binocular-guided 3D Gaussian splatting with self-supervision generates high-quality novel views from sparse inputs without external priors, significantly outperforming state-of-the-art methods.

A novel model reveals how hippocampal-entorhinal circuits use compositional coding and modular attractor networks to enable robust and flexible spatial representation, advancing our understanding of c…

This paper presents a novel algorithm for binary search using distributional predictions, achieving optimal query complexity O(H(p) + log n) and demonstrating enhanced robustness against prediction er…

BI-DiffSR, a novel binarized diffusion model, achieves high-quality image super-resolution with significantly reduced memory and computational costs, outperforming existing methods.

Bileve: a novel bi-level signature secures text provenance in LLMs against spoofing, enhancing detectability and reliability via fine-grained integrity checks and coarse-grained source tracing.

BiDM achieves full 1-bit quantization in diffusion models, significantly improving storage and speed without sacrificing image quality, setting a new state-of-the-art.

GPTrack: A novel unsupervised framework enhances cardiac motion tracking by using sequential Gaussian processes and bidirectional recurrence, improving accuracy and efficiency.