Tootfinder

Can We Reliably Rank Model Performance across Domains without Labeled Data?
Veronica Rammouz, Aaron Gonzalez, Carlos Cruzportillo, Adrian Tan, Nicole Beebe, Anthony Rios
https://arxiv.org/abs/2510.09519

Can We Reliably Rank Model Performance across Domains without Labeled Data?
Estimating model performance without labels is an important goal for understanding how NLP models generalize. While prior work has proposed measures based on dataset similarity or predicted correctness, it remains unclear when these estimates produce reliable performance rankings across domains. In this paper, we analyze the factors that affect ranking reliability using a two-step evaluation setup with four base classifiers and several large language models as error predictors. Experiments on t…

:range_de_chin_shite_oven_de_bun_suru:

Combining Knowledge Graphs and NLP to Analyze Instant Messaging Data in Criminal Investigations
Riccardo Pozzi, Valentina Barbera, Renzo Alva Principe, Davide Giardini, Riccardo Rubini, Matteo Palmonari
https://arxiv.org/abs/2509.26487

Combining Knowledge Graphs and NLP to Analyze Instant Messaging Data in Criminal Investigations
Criminal investigations often involve the analysis of messages exchanged through instant messaging apps such as WhatsApp, which can be an extremely effort-consuming task. Our approach integrates knowledge graphs and NLP models to support this analysis by semantically enriching data collected from suspects' mobile phones, and help prosecutors and investigators search into the data and get valuable insights. Our semantic enrichment process involves extracting message data and modeling it using a …

NLP Methods for Detecting Novel LLM Jailbreaks and Keyword Analysis with BERT
John Hawkins, Aditya Pramar, Rodney Beard, Rohitash Chandra
https://arxiv.org/abs/2510.01644 https:…

NLP Methods for Detecting Novel LLM Jailbreaks and Keyword Analysis with BERT
Large Language Models (LLMs) suffer from a range of vulnerabilities that allow malicious users to solicit undesirable responses through manipulation of the input text. These so-called jailbreak prompts are designed to trick the LLM into circumventing the safety guardrails put in place to keep responses acceptable to the developer's policies. In this study, we analyse the ability of different machine learning models to distinguish jailbreak prompts from genuine uses, including looking at our abi…

Mining the Mind: What 100M Beliefs Reveal About Frontier LLM Knowledge
Shrestha Ghosh, Luca Giordano, Yujia Hu, Tuan-Phong Nguyen, Simon Razniewski
https://arxiv.org/abs/2510.07024

Mining the Mind: What 100M Beliefs Reveal About Frontier LLM Knowledge
LLMs are remarkable artifacts that have revolutionized a range of NLP and AI tasks. A significant contributor is their factual knowledge, which, to date, remains poorly understood, and is usually analyzed from biased samples. In this paper, we take a deep tour into the factual knowledge (or beliefs) of a frontier LLM, based on GPTKB v1.5 (Hu et al., 2025a), a recursively elicited set of 100 million beliefs of one of the strongest currently available frontier LLMs, GPT-4.1. We find that the mode…

🇺🇦 #NowPlaying on #BBC6Music's #AmyLamé
St. Vincent:
🎵 Pay Your Way In Pain
#StVincent
https://stvincent.bandcamp.com/track/pay-your-way-in-pain-idles-remix
https://open.spotify.com/track/1nLaoWVhNRZ38irY0LZjL6

🇺🇦 #NowPlaying on #BBC6Music's #CerysMatthews
St. Vincent:
🎵 Pay Your Way In Pain
#StVincent
https://stvincent.bandcamp.com/track/pay-your-way-in-pain-idles-remix
https://open.spotify.com/track/1nLaoWVhNRZ38irY0LZjL6

🇺🇦 #NowPlaying on #BBC6Music's #CerysMatthews
St. Vincent:
🎵 Pay Your Way In Pain
#StVincent
https://stvincent.bandcamp.com/track/pay-your-way-in-pain-idles-remix
https://open.spotify.com/track/1nLaoWVhNRZ38irY0LZjL6