Discover-Tech’s Controlium platform enables partners to de-anonymize and fingerprint devices, automatically infecting them the moment an advertisement is rendered.
The report concludes that online ads represent a cybersecurity crisis, highlighting structural flaws in the advertising system that failed to detect such abuse.
The preprint authors report: The nuclear Argonaute HRDE-1 uses an RGG domain to broadly interact with euchromatin, enabling transgenerational epigenetic silencing and germline immortality in C. elegans.
Authors propose that this initial siRNA-independent chromatin entry allows HRDE-1 to access active transcription compartments for effective gene silencing.
The preprint authors report: LIBERO-PeRM is a benchmark for preference learning in embodied agents that studies five questions including zero-shot policy behavior and generalization across layouts.
Experiments show current VLA policies struggle with zero-shot personalization while SFT makes preferences learnable, though mixed training can weaken motion-preference learning.
Three developments worth your time
For people evaluating this workarticle
AdFection: Targeted ads turned into a pipeline for zero-click mercenary spyware
Discover-Tech’s Controlium platform enables partners to de-anonymize and fingerprint devices, automatically infecting them the moment an advertisement is rendered.
See supporting passage
Discover-Tech operates a platform called Controlium that enables its mercenary partners to de-anonymize, fingerprint, and automatically infect devices the moment an advertisement is rendered — a form of zero-click attack.
The report concludes that online ads represent a cybersecurity crisis, highlighting structural flaws in the advertising system that failed to detect such abuse.
See supporting passage
Discover-Tech’s mass abuse, privacy invasion, and facilitation for mercenary spyware attacks illustrates structural flaws with the online advertising system, which failed to detect or prevent the abuse documented in this report.
For engineers evaluating energy technologiespreprint
The nuclear Argonaute HRDE-1 broadly interacts with euchromatin via an RGG domain to enable transgenerational epigenetic silencing
The preprint authors report: The nuclear Argonaute HRDE-1 uses an RGG domain to broadly interact with euchromatin, enabling transgenerational epigenetic silencing and germline immortality in C. elegans.
See supporting passage
we found that an intrinsically disordered arginine-glycine-glycine (RGG) domain in HRDE-1 is essential for siRNA-guided transgenerational epigenetic silencing and germline immortality.
Authors propose that this initial siRNA-independent chromatin entry allows HRDE-1 to access active transcription compartments for effective gene silencing.
See supporting passage
We propose that the initial siRNA-independent, RGG-dependent HRDE-1-chromatin interaction enables HRDE-1 to enter the transcribing chromatin compartment, a likely prerequisite for the subsequent siRNA-pre-mRNA interaction.
Compare the study’s reported findings and evaluation conditions with the evidence it presents. Use the question below to check what remains untested before applying the findings.
Editorial suggestion
Keep in mind
A preprint reports the authors’ findings; peer review and independent replication are not established here.
The preprint authors report: LIBERO-PeRM is a benchmark for preference learning in embodied agents that studies five questions including zero-shot policy behavior and generalization across layouts.
See supporting passage
We introduce LIBERO-PeRM, a benchmark for preference learning in embodied agents. LIBERO-PeRM studies five questions: 1) how policies follow preferences in zero-shot settings; 2) how they learn single preferences from demonstrations; 3) how efficiently they acquire preferences as demonstrations increase; 4) how learned preferences generalize across layouts and tasks; and 5) how policies compose preferences and behave under conflicts.
Experiments show current VLA policies struggle with zero-shot personalization while SFT makes preferences learnable, though mixed training can weaken motion-preference learning.
See supporting passage
Experiments show that current VLA policies struggle with zero-shot personalization, while SFT makes preferences learnable. Mixed training achieves better no-preference retention than sequential adaptation and improves performance with contextual prompts compared with preference-only training, but can weaken motion-preference learning; preference generalization, decomposition, and conflict handling remain difficult.
Compare the study’s reported findings and evaluation conditions with the evidence it presents. Use the question below to check what remains untested before applying the findings.
Editorial suggestion
Keep in mind
A preprint reports the authors’ findings; peer review and independent replication are not established here.
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