· ai
[Paper] AirSim360: A Panoramic Simulation Platform within Drone View
The field of 360-degree omnidirectional understanding has been receiving increasing attention for advancing spatial intelligence. However, the lack of large-sca...
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- · ai
[Paper] The Art of Scaling Test-Time Compute for Large Language Models
Test-time scaling (TTS) -- the dynamic allocation of compute during inference -- is a promising direction for improving reasoning in large language models (LLMs...
- · ai
[Paper] MV-TAP: Tracking Any Point in Multi-View Videos
Multi-view camera systems enable rich observations of complex real-world scenes, and understanding dynamic objects in multi-view settings has become central to ...
- · ai
[Paper] Learning Visual Affordance from Audio
We introduce Audio-Visual Affordance Grounding (AV-AG), a new task that segments object interaction regions from action sounds. Unlike existing approaches that ...
- · ai
[Paper] AlignSAE: Concept-Aligned Sparse Autoencoders
Large Language Models (LLMs) encode factual knowledge within hidden parametric spaces that are difficult to inspect or control. While Sparse Autoencoders (SAEs)...
- · ai
[Paper] Learning Sim-to-Real Humanoid Locomotion in 15 Minutes
Massively parallel simulation has reduced reinforcement learning (RL) training time for robots from days to minutes. However, achieving fast and reliable sim-to...
- · ai
[Paper] RoaD: Rollouts as Demonstrations for Closed-Loop Supervised Fine-Tuning of Autonomous Driving Policies
Autonomous driving policies are typically trained via open-loop behavior cloning of human demonstrations. However, such policies suffer from covariate shift whe...
- · ai
[Paper] LLM CHESS: Benchmarking Reasoning and Instruction-Following in LLMs through Chess
We introduce LLM CHESS, an evaluation framework designed to probe the generalization of reasoning and instruction-following abilities in large language models (...
- · ai
[Paper] Forecasting in Offline Reinforcement Learning for Non-stationary Environments
Offline Reinforcement Learning (RL) provides a promising avenue for training policies from pre-collected datasets when gathering additional interaction data is ...
- · ai
[Paper] A robust generalizable device-agnostic deep learning model for sleep-wake determination from triaxial wrist accelerometry
Study Objectives: Wrist accelerometry is widely used for inferring sleep-wake state. Previous works demonstrated poor wake detection, without cross-device gener...
- · ai
[Paper] Feature-Based Semantics-Aware Scheduling for Energy-Harvesting Federated Learning
Federated Learning (FL) on resource-constrained edge devices faces a critical challenge: The computational energy required for training Deep Neural Networks (DN...
- · ai
[Paper] Chain-of-Ground: Improving GUI Grounding via Iterative Reasoning and Reference Feedback
GUI grounding aims to align natural language instructions with precise regions in complex user interfaces. Advanced multimodal large language models show strong...