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Language Model Networks: Supervision-Efficient Learning through Dense Communication
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Port React Compiler to Rust
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And nobody gives a single fuck how it's built anymore. The previous motherfuckers spent a decade teaching you the holy commandments of clean code. I have, begrudgingly, honored every one of them on this page, because the agent did it in one shot while I was on the toilet: clamp() .lang attribute and all.
Devs know AI code is riddled with holes, but ship it anyway
Research by AppSec biz Checkmarx finds that 70 percent of developers believe AI-generated code has more vulnerabilities, and 30 percent knowingly ship vulnerable code into production. The report is based on responses from 2,350 global developers, CISOs, and AppSec managers, and follows similar annual surveys since 2023. The number of respondents is 54 percent higher this year than last, and the increased sample size may account for a somewhat surprising statistic: the reported proportion of...
Towards Fair Graph Prompting: A Dual-Prompt Mechanism for Mitigating Attribute and Structural Bias
Announce Type: replace Abstract: Self-supervised pre-training on unlabeled graph data has become a common paradigm for Graph Neural Networks (GNNs). However, an objective gap often remains between pre-training objectives and downstream tasks. To bridge this gap, graph prompting methods adapt frozen pre-trained GNNs to specific downstream tasks through learnable prompts.
GAPVD1 regulates CSNK1D-dependent PER2 FASP phosphorylation
The mammalian circadian clock relies on precisely timed transcriptional and post-translational events to generate ~24-hour rhythms. A key post-translational mechanism is phosphorylation of PER2 by CSNK1D, governed by a phosphoswitch that integrates stabilizing and destabilizing phosphorylation marks at the FASP and Degron sites to control PER2 stability and circadian period. Here, a novel role for the PER complex protein GAPVD1 in regulating CSNK1D-mediated FASP site phosphorylation is revealed.
Theta phase and theta-gamma coupling organise the spoken language network
Speech production requires rapid coordination of conceptual and lexical processes across distributed cortical networks, yet the neurophysiological mechanisms enabling this coordination remain poorly understood. Oscillatory coupling has emerged as a candidate mechanism for coordinating neural activity across spatial scales. Here, we used whole-head magnetoencephalography during overt picture naming to test how phase and phase-amplitude coupling organise neural dynamics preceding articulation.
Balancing Symmetry and Efficiency in Graph Flow Matching
Announce Type: replace Abstract: Equivariance is central to graph generative models, as it ensures the model respects the permutation symmetry of graphs. However, strict equivariance can increase computational cost due to added architectural constraints, and can slow down convergence because the model must be consistent across a large space of possible node permutations. We study this trade-off for graph generative models.
StainFlow: Entity-Stain Tracking and Evidence Linking for Process Rewards in GUI Agents
arXiv:2606.07027v1 Announce Type: new Abstract: Reinforcement Learning (RL) has become a promising approach for improving GUI Agents in long-horizon, stochastic digital environments, but trajectory-level success feedback is too sparse to provide reliable credit assignment for intermediate exploration steps. To mitigate this issue, recent studies introduce Process Reward Models (PRMs), which provide finer-grained training feedback through global milestone verification or local step-level...