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Testing General Relativity Through Gravitational Wave Classification: A Convolutional Neural Network Framework

- We present a machine learning framework for testing general relativity (GR) with gravitational wave signals from binary black hole mergers. Using the source parameters of 173 BBH events from the GWTC...

Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models

- We present an experimental study of energy-to-solution (ETS) of hybrid quantum-classical applications, enabled by direct instrumentation of power consumption of a Forte Enterprise trapped-ion quantum...

Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms

- Distributed quantum algorithms offer a promising pathway to scale variational quantum algorithms beyond the constraints of noisy intermediate-scale quantum hardware. However, existing approaches...

EgoForce: Forearm-Guided Camera-Space 3D Hand Pose from a Monocular Egocentric Camera

- Reconstructing the absolute 3D pose and shape of the hands from the user's viewpoint using a single head-mounted camera is crucial for practical egocentric interaction in AR/VR, telepresence, and...

LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues

- Long-term memory is crucial for agents in specialized web environments, where success depends on recalling interface affordances, state dynamics, workflows, and recurring failure modes. However,...

CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives

- Autoregressive video generation aims at real-time, open-ended synthesis. Yet, cinematic storytelling is not merely the endless extension of a single scene; it requires progressing through evolving...

Elastic Attention Cores for Scalable Vision Transformers

- Vision Transformers (ViTs) achieve strong data-driven scaling by leveraging all-to-all self-attention. However, this flexibility incurs a computational cost that scales quadratically with image...

Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training

- In settings where labeled verifiable training data is the binding constraint, each checked example should be allocated carefully. The standard practice is to use this data directly on the model that...

OmniNFT: Modality-wise Omni Diffusion Reinforcement for Joint Audio-Video Generation

- Recent advances in joint audio-video generation have been remarkable, yet real-world applications demand strong per-modality fidelity, cross-modal alignment, and fine-grained synchronization....

ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents

- Computer Use Agents (CUAs) can act through both atomic GUI actions, such as click and type, and high-level tool calls, such as API-based file operations, but this hybrid action space often leaves...

Reward Hacking in Rubric-Based Reinforcement Learning

- Reinforcement learning with verifiable rewards has enabled strong post-training gains in domains such as math and coding, though many open-ended settings rely on rubric-based rewards. We study reward...

Routers Learn the Geometry of Their Experts: Geometric Coupling in Sparse Mixture-of-Experts

- Sparse Mixture-of-Experts (SMoE) models enable scaling language models efficiently, but training them remains challenging, as routing can collapse onto few experts and auxiliary load-balancing losses...

A Causal Language Modeling Detour Improves Encoder Continued Pretraining

- When adapting an encoder to a new domain, the standard approach is to continue training with Masked Language Modeling (MLM). We show that temporarily switching to Causal Language Modeling (CLM)...

Basilisk and Docker for Reproducible GN&C Simulation: A Workflow Reference

- Basilisk is an open-source astrodynamics simulation framework widely used for spacecraft guidance, navigation, and control (GN&C) research and development. Despite its flexibility and...

ORCE: Order-Aware Alignment of Verbalized Confidence in Large Language Models

- Large language models (LLMs) often produce answers with high certainty even when they are incorrect, making reliable confidence estimation essential for deployment in real-world scenarios. Verbalized...

LychSim: A Controllable and Interactive Simulation Framework for Vision Research

- While self-supervised pretraining has reduced vision systems' reliance on synthetic data, simulation remains an indispensable tool for closed-loop optimization and rigorous out-of-distribution...

GaitProtector: Impersonation-Driven Gait De-Identification via Training-Free Diffusion Latent Optimization

- Conventional gait de-identification methods often encounter an inherent trade-off: they either provide insufficient identity suppression or introduce spatiotemporal distortions that impede...

Enhancing Instruction Prefetching via Cache and TLB Management

- Modern server workloads exhibit massive instruction footprints that heavily pressure the processor front-end, making L1 instruction (L1I) prefetching critical for sustaining performance. However,...

KV-Fold: One-Step KV-Cache Recurrence for Long-Context Inference

- We introduce KV-Fold, a simple, training-free long-context inference protocol that treats the key-value (KV) cache as the accumulator in a left fold over sequence chunks. At each step, the model...

Solve the Loop: Attractor Models for Language and Reasoning

- Looped Transformers offer a promising alternative to purely feed-forward computation by iteratively refining latent representations, improving language modeling and reasoning. Yet recurrent...

Search Your Block Floating Point Scales!

- Quantization has emerged as a standard technique for accelerating inference for generative models by enabling faster low-precision computations and reduced memory transfers. Recently, GPU...