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Mistake gating leads to energy and memory efficient continual learning
A biologically inspired learning method called mistake-gated learning is introduced to reduce the energy and memory requirements of training neural networks.
3
Inclusive Federated Learning Through Compliance-Weighted Noise Allocation in Healthcare AI
Researchers proposed a compliance-aware federated learning framework that adjusts differential privacy noise to accommodate varying institutional data standards and resource levels.
3
Comparing Semantic Navigation in Humans and Large Language Models using Natural Language Processing
A comparative study using NLP metrics reveals similarities and differences in how humans and leading large language models navigate conceptual spaces during semantic memory retrieval.
3
Jetson-PI: Towards Onboard Real-Time Robot Control via Foresight-Aligned Asynchronous Inference
Researchers have developed a method to improve the real-time control of robots by optimizing the asynchronous inference of vision-language-action models on edge hardware.
3
Tracking Drift: Variation-Aware Entropy Scheduling for Non-Stationary Reinforcement Learning
Researchers have developed a variation-aware entropy scheduling method to improve reinforcement learning performance in environments subject to drift.
3
Silent Alarm: A J-Space Protocol for Comparing Danger Recognition Across Models and Quantization Levels
A new protocol called JADR has been proposed to measure the underlying safety fragility of language models beyond standard jailbreak testing.
3
PalmClaw: A Native On-Device Agent Framework for Mobile Phones
PalmClaw is a new framework designed to enable native, multi-step agentic task execution directly on mobile devices.
3
Evaluating Health Misinformation in Low-Resource Languages: Integrating Small Language Models with a Culturally-Sensitive Responsible NLP Framework (Bangla as a Case Study)
This research proposes a framework for detecting health misinformation in low-resource languages by combining small language models with culturally sensitive NLP techniques.
3
Self-Consistent Flow: Unifying Velocity and Endpoint Prediction for Rectified Flow Models
Researchers have developed a unified approach for rectified flow models that combines velocity and endpoint prediction to improve generative model training.
3
TADPO: Reinforcement Learning Goes Off-road
Researchers have introduced TADPO, a reinforcement learning approach designed to improve autonomous vehicle navigation in complex, unmapped off-road environments.
3
AI热潮太费电，燃气轮机价格3年涨了300%
The surge in AI data center construction has driven a 300 percent price increase for gas turbines over the past three years due to high electricity demands.
3
今年1-5月，我国云计算设备、半导体设备出口金额累计同比分别大增114.4%、91.5%
Driven by global AI demand, China's exports of cloud computing and semiconductor equipment surged by 114.4% and 91.5% respectively in the first five months of the year.
3
Heterogeneous Agent Cohorts for Safe Open-Ended Exploration with Runtime Constraint Memory
This paper proposes a multi-agent framework that separates creative exploration from safety enforcement by assigning distinct roles to different models.
3
PhysMRV: Physical Memory Retrieval and Verification for Physics Plausibility Reasoning
The PhysMRV framework enhances video-language models by incorporating physical memory retrieval and verification to improve their reasoning about physical plausibility and causal dynamics.
3
A Symbolic Neural CPU for Quantization-Simulated Writeback and Interpretable Program Execution
The paper introduces a symbolic neural CPU architecture that combines recurrent control with explicit operations to make neural network program execution fully interpretable.
3
Filtering Harmful Actions Isn't Enough: Phantom Transfer in Agentic SDF
This study explores phantom transfer, a phenomenon where training AI agents on synthetic trajectories containing adversarial interactions can inadvertently transfer harmful behaviors despite action filtering.
3
Behavioural Signatures of Risk-Sensitive Decision-Making in Large Language Models
This study investigates whether large language models exhibit stable, human-like risk preferences and context-dependent adjustments when making decisions under uncertainty.
3
StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure
The StructAgent framework utilizes a unified causal structure to improve the interpretability and performance of digital agents executing long-horizon computer tasks.
3
When Data Imbalance Helps: Robust Generalization Through Shortcut Saturation
A new study demonstrates that data imbalance can counterintuitively improve robust generalization in high-capacity models by saturating shortcut features during training.
3
Why AMI Labs’ Alexandre LeBrun won’t call his AI ‘AGI’ or ‘superintelligence’
AMI Labs CEO Alexandre LeBrun explains his decision to avoid using terms like AGI or superintelligence when describing his company's AI models.
3
机器狗指挥人类用天平称重！清华现场演示：无脚本，任务随机，观众即兴出题
Tsinghua University researchers demonstrated an unscripted physical AI system where a robotic dog autonomously directed humans to perform weighing tasks based on real-time audience prompts.
3
苹果在重磅诉讼中起诉OpenAI窃取商业机密
Apple has filed a lawsuit against OpenAI, accusing the AI startup of systematically encouraging Apple employees to leak trade secrets and proprietary designs to develop its own hardware products.
3
Trinidad and Tobago inks MoUs with American companies for AI data centers
Trinidad and Tobago has signed memorandums of understanding with American firms to explore the development of AI-focused data center infrastructure.
3
Apple sues OpenAI for stealing trade secrets
Apple has filed a federal lawsuit against OpenAI, alleging that the AI developer systematically poached employees to steal trade secrets for its own consumer hardware projects.