Carlos's Debrief

June 12, 2026 19:00
0ArXiv Papers
18Web Findings
18Total Sources
Topics searched: Artificial Intelligence Machine Learning Large Language Models Security & Cybersecurity Cryptography Zero Knowledge Quantum Computing Crypto & Blockchain AI Agents & Reasoning AI Safety & Alignment
June 12, 2026 19:00 — Curated by Hermes Research Scout

⚡ Quick Summary

📰 News Headlines

🌐 Web Findings

🤗 HuggingFace Papers 7

WebChallenger: A Reliable and Efficient Generalist Web Agent [7]
Autonomous web navigation remains challenging for LLM agents, and the strongest generalist systems rely on proprietary reasoning models whose inference cost is prohibitive for the…
HuggingFace Papers
Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs [9]
Modern LLM training pipelines increasingly rely on other models to generate data, filter corpora, judge outputs, and guide development decisions. These dependencies are recursive:…
▲ 2HuggingFace Papers
See What I See, Know What I Think: Dense Latent Communication Across Heterogeneous Agents [5]
Multi-agent systems communicate mostly through text, paying a lossy and expensive decode and re-encode cost. KV-cache communication is a promising alternative, yet most prior work…
▲ 1HuggingFace Papers
On the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task Performance [3]
Large Language Models (LLMs) are increasingly used for zero-shot annotation and LLM-as-a-judge tasks, yet their reliability hinges on how model-internalized priors interact with…
HuggingFace Papers
Getting Better at Working With You: Compiling User Corrections into Runtime Enforcement for Coding Agents [6]
Interactive LLM agents are becoming part of daily work, but they do not reliably become easier to work with over time: a correction remembered in one session may still be violated…
▲ 1HuggingFace Papers
Where, What, Why, and Importance: Structured Defect Grounding for Text-to-Image Feedback [8]
Despite generating increasingly photorealistic images, text-to-image (T2I) models still exhibit localized, subtle, and structurally complex failures. Diagnosing these failures…
▲ 13HuggingFace Papers
Rethinking Psychometric Evaluation of LLMs: When and Why Self-Reports Predict Behavior [4]
Anticipating LLM behavioral tendencies from low-cost psychometric probes is critical for safe deployment, but only if self-reports (SR) reliably predict behavior. Recent work…
▲ 2HuggingFace Papers

🧪 Semantic Scholar 1

<inline-formula><tex-math notation="LaTeX">$ \tt {zkFL}$</tex-math><alternatives><mml:math><mml:mi mathvariant="monospace">zkFL</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq1-3403370.gif"/></alternatives></inline-formula>: Zero-Knowledge Proof-Based Gradient Aggregation for Federated Learn [16]
Federated learning (FL) is a machine learning paradigm, which enables multiple and decentralized clients to collaboratively train a model under the orchestration of a central…
📊 21 citesSemantic Scholar

📝 OpenReview 2

SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression [17]
The advancements in Large Language Models (LLMs) have been hindered by their substantial sizes, which necessitate LLM compression methods for practical deployment. Singular Value…
OpenReview
Diffusion$^2$: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models [18]
Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and…
OpenReview

🦞 Lobste.rs 2

What’s New in WeatherMesh-6 [1]
| WindBorne | What’s New in WeatherMesh-6
Lobste.rs
ChatGPT Won't Let You Type Until Cloudflare Reads Your React State. I Decrypted the Program That Does It [2]
Edit April 2, 2026: I've been getting inbound interest from researchers wanting to run their own queries. The MCP integration I use for my own research lets you analyze live…
Lobste.rs

🎓 Google Scholar 6

Large language models (LLM) in computational social science: prospects, current state, and challenges [12]
Finding from 🎓 Google Scholar.
Google Scholar
Securing the future: exploring post-quantum cryptography for authentication and user privacy in IoT devices [14]
Cluster Computing - With the emergence of quantum computers, traditional cryptographic methods are vulnerable to attacks, emphasizing the need for post-quantum cryptography to…
Google Scholar
Quantum machine learning: A comprehensive review of integrating AI with quantum computing for computational advancements [15]
Finding from 🎓 Google Scholar.
Google Scholar
Artificial intelligence and machine learning in cybersecurity: a deep dive into state-of-the-art techniques and future paradigms [13]
Finding from 🎓 Google Scholar.
Google Scholar
Early identification of breakthrough technologies: Insights from science-driven innovations [10]
Finding from 🎓 Google Scholar.
Google Scholar
Catalyst breakthroughs in methane dry reforming: Employing machine learning for future advancements [11]
Finding from 🎓 Google Scholar.
Google Scholar

🔗 All Sources

  1. [1] What’s New in WeatherMesh-6
  2. [2] ChatGPT Won't Let You Type Until Cloudflare Reads Your React State. I Decrypted the…
  3. [3] On the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task…
  4. [4] Rethinking Psychometric Evaluation of LLMs: When and Why Self-Reports Predict Behavior
  5. [5] See What I See, Know What I Think: Dense Latent Communication Across Heterogeneous Agents
  6. [6] Getting Better at Working With You: Compiling User Corrections into Runtime Enforcement…
  7. [7] WebChallenger: A Reliable and Efficient Generalist Web Agent
  8. [8] Where, What, Why, and Importance: Structured Defect Grounding for Text-to-Image Feedback
  9. [9] Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs
  1. [10] Early identification of breakthrough technologies: Insights from science-driven…
  2. [11] Catalyst breakthroughs in methane dry reforming: Employing machine learning for future…
  3. [12] Large language models (LLM) in computational social science: prospects, current state,…
  4. [13] Artificial intelligence and machine learning in cybersecurity: a deep dive into…
  5. [14] Securing the future: exploring post-quantum cryptography for authentication and user…
  6. [15] Quantum machine learning: A comprehensive review of integrating AI with quantum computing…
  7. [16] <inline-formula><tex-math notation="LaTeX">$ \tt…
  8. [17] SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model…
  9. [18] Diffusion$^2$: Dynamic 3D Content Generation via Score Composition of Video and…
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