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Never miss a research paper that matters to you. Paperzilla scans arXiv, bioRxiv, medRxiv, etc., daily, classifies must-read papers, and emails you a digest.

Joined October 2024
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Oh my, the Clawdfather reposted it! You're welcome, @pors, for me finding this paper (which is my job).
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Imagine two people talking at the same time, but you want a clean audio signal from just the one you "select". This paper describes a system that, after you select the desired speaker, extracts the correct audio using lip movements. Not sure how useful this is, but pretty cool nonetheless. Read 👀👇
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Find relevant new papers and discuss them with your fav AI agent in a morning brief, just like Mark. Link below 👇
The good, bad and ugly of open-weight models: Good: run it, study it, nobody can take it away. Bad: attackers can fine-tune the guardrails away. Ugly: LLMs are hard to patch and you can’t control downloaded copies. That is the ultra-short takeaway of this fascinating paper. Link below 👇
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Hey, look, preprint paper growth accelerates with the introduction of AI agents! There is only one way to fight this: with your agent! The Paperzilla research brief exists just for that. Link in comment.
"Is the arXiv Apocalypse upon us? A break in preprint growth coincident with agentic AI" That is the title of a new paper I found in my morning brief, so of course I had to have a closer look. A couple of findings: - Solo-authored papers increased by 70% in mathematics and 71% in condensed matter between 2025 and 2026. - Submission volume in October 2026 reached 14% above the October 2025 total by the 23rd of the month. - Preparation time for the study dropped from an estimated working week to 3.75 hours using agentic tools. Link below 👇
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An interesting paper by Apple Research arrived in my morning brief. They describe the training of a small model that can run on the iPhone to help an agent navigate iOS apps. Say, computer-use for iPhones. One finding I found funny: rewarding each successful step made the model drag out the journey, even when it could have gone straight to completing the final task. More interesting findings in the paper 👇
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Keeping up to date with the latest progress on your research topic is now easy. Paperzilla is now officially in the Claude directory! This gives you morning briefs on new research that matter to you: - just the relevant papers - a short explanation of why it is relevant to you - ready to discuss the papers inside Claude
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You may have heard of decision models like Jev. These models are classifiers where the classes are provided together with the query. As opposed to classifiers that were trained for a fixed set of classes. I found this preprint paper where Jev and OpenAI decision models are used to make health recommendations. It shows that adding information to a patient's medical facts can strongly influence the decision models' choices. For example: 1. Jev reads the case. A patient has a minor hand burn. Jev gives a 4% probability of recommending a mental-health assessment. 2. A social label is added. Describing the patient as belonging to a minority or historically marginalized group pushes that probability to 82%, although “No psychiatric findings were added.” In this experiment, an LLM was added to judge whether the added information is actual medical information the decision model should incorporate. Pretty fascinating, right? Read the full paper 👇
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When agents attack your infra, you want agents to defend as well. I found an interesting research paper on this subject; open-source code included! These defense agents (actually, the model) are trained with RL to behave in specific ways based on what they experience during an attack. In this paper, the researchers propose a method to customize the agent's behavior to its environment. This deterministic "switch" can improve results without fine-tuning or retraining the model. Read all about it in the paper and check out the source code on github 👇
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Paperzilla has seven sources now! Another research topic or source you'd like to see? Let me know!
IACR ePrint is now a Paperzilla source! More vulnerabilities than ever, so it's a good time to add another research paper (preprint) source for cryptology. Read the full announcement 👇
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For a middle manager or podcaster, using the term "Red Teaming" is second nature nowadays. So when a paper pops up with "Self-Improved Red Teaming" in the title, we need to take a look, right? So Red Teaming is simply trying to find vulnerabilities in your own systems before others do. Read on 👇
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IACR ePrint is now a Paperzilla source! More vulnerabilities than ever, so it's a good time to add another research paper (preprint) source for cryptology. Read the full announcement 👇
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Are you thinking, "Interesting, but do I have to read all this to make sure it is relevant to me"? Paperzilla can help you out with: - a summary that lists everything you need to know before reading the paper (or not) - integrating relevant papers with your AI agent workflow
TIL that you can embed a hidden backdoor in an encryption algorithm. This happens in the real world, too: in 2006, a random number generator algorithm even made it into a NIST standard and stayed that way until 2014... A new research paper describes a method to find these hidden backdoors (for some types of cryptography). Read all about it below vvv
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This is the second paper in our cybersecurity research week of new preprints. This gives a bit of insight into the "OMG NEW MATH PROOFS WILL BREAK CRYPTOGRAPHY" panic. 👀
Lately, people have gotten a bit stressed about AI-driven advances in math research. What if it makes cryptography weak? I personally don't think it is that easy, but this new paper shows there is something to it: a new mathematical approach (by humans in this case) made a cipher significantly weaker. Read the paper 👇
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Just as minor vulnerabilities can be chained, combining clean skills can lead to your agent being vulnerable to it.
Auditing the AI skills you use for potential vulnerabilities is a good practice, but what if it isn't enough? A new paper shows that two "clean" skills can become a security risk when an agent combines them. The researchers give a simple example: - One AI skill reads your email. - Another skill sends emails on your behalf. - An attacker sends you an email instructing the agent to forward confidential information. - The AI reads the malicious instruction and uses its second skill to leak the information. Read the full paper below.
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Not all agentic cyber attacks come from the outside. Insider AI agents can go rogue as well. This report proposes the use of honeypots to alert security staff of insider threats Read the full report 👇
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What if your AI agent has overlapping skills? For a specific task, two skills are candidates. A new study shows that only one skill is used, and the other is ignored, so instructions in the second skill are lost. The paper shows that pre-compiling overlapping skills in a single skill increases accuracy. Read it 👇
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Is this the future of academic papers? In this paper, researchers propose a format for papers so that AI agents can process them more easily (fewer tokens!). Link to the study below 👀👇
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If you keep ignoring your Google Scholar alerts, it might be time for a better reading list. We look at two ways to get one: DIY with an AI agent or Paperzilla. Link below 👇
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