Tootfinder

This https://arxiv.org/abs/2502.04951 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Unsafe LLM-Based Search: Quantitative Analysis and Mitigation of Safety Risks in AI Web Search
Recent advancements in Large Language Models (LLMs) have significantly enhanced the capabilities of AI-Powered Search Engines (AIPSEs), offering precise and efficient responses by integrating external databases with pre-existing knowledge. However, we observe that these AIPSEs raise risks such as quoting malicious content or citing malicious websites, leading to harmful or unverified information dissemination. In this study, we conduct the first safety risk quantification on seven production AI…

HotelMatch-LLM: Joint Multi-Task Training of Small and Large Language Models for Efficient Multimodal Hotel Retrieval
Arian Askari, Emmanouil Stergiadis, Ilya Gusev, Moran Beladev
https://arxiv.org/abs/2506.07296

HotelMatch-LLM: Joint Multi-Task Training of Small and Large Language Models for Efficient Multimodal Hotel Retrieval
We present HotelMatch-LLM, a multimodal dense retrieval model for the travel domain that enables natural language property search, addressing the limitations of traditional travel search engines which require users to start with a destination and editing search parameters. HotelMatch-LLM features three key innovations: (1) Domain-specific multi-task optimization with three novel retrieval, visual, and language modeling objectives; (2) Asymmetrical dense retrieval architecture combining a small …

Understanding Mental Models of Generative Conversational Search and The Effect of Interface Transparency
Chadha Degachi, Samuel Kernan Freire, Evangelos Niforatos, Gerd Kortuem
https://arxiv.org/abs/2506.03807

Understanding Mental Models of Generative Conversational Search and The Effect of Interface Transparency
The experience and adoption of conversational search is tied to the accuracy and completeness of users' mental models -- their internal frameworks for understanding and predicting system behaviour. Thus, understanding these models can reveal areas for design interventions. Transparency is one such intervention which can improve system interpretability and enable mental model alignment. While past research has explored mental models of search engines, those of generative conversational search re…

trec_web: TREC WT10g (2003)
A web graph network originally constructed in 2003 as a testbed for information-retrieval techniques, including web search engines. Distributed by University of Glasgow.
This network has 1601787 nodes and 8063026 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net…

Modern search demands scalable personalisation. Join Piotr Kobziakowski
at this year's Berlin Buzzwords to discover how Vespa's multi-stage ranking and tensor framework can be used for hybrid queries, multimodal retrieval, and real-time machine learning. Learn how to deploy low-latency, high-relevance search systems at petabyte scale.
Learn more:

Vespa.ai’s Personalized Search: Advanced Ranking & Tensor framework
Today’s applications require search engines to unify text, vectors, and business logic with millisecond latency at petabyte scale. It’s not easy to balance speed, relevance, and personalization for a large user population and a billion scale item base. Vespa.ai, the open-source engine powering Yahoo, Perplexity, Qwant, Vinted, Spotify addresses this through multi-stage ranking with close to data tensor operations and easy to understand custom functions. Vespa’s phased architecture enables…

Hiding in Plain Sight: Query Obfuscation via Random Multilingual Searches
Anton Firc, Jan Klus\'a\v{c}ek, Kamil Malinka
https://arxiv.org/abs/2506.04963

Hiding in Plain Sight: Query Obfuscation via Random Multilingual Searches
Modern search engines extensively personalize results by building detailed user profiles based on query history and behaviour. While personalization can enhance relevance, it introduces privacy risks and can lead to filter bubbles. This paper proposes and evaluates a lightweight, client-side query obfuscation strategy using randomly generated multilingual search queries to disrupt user profiling. Through controlled experiments on the Seznam.cz search engine, we assess the impact of interleaving…

This https://arxiv.org/abs/2504.14870 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Acting Less is Reasoning More! Teaching Model to Act Efficiently
Tool-integrated reasoning (TIR) augments large language models (LLMs) with the ability to invoke external tools during long-form reasoning, such as search engines and code interpreters, to solve tasks beyond the capabilities of internal reasoning. While reinforcement learning (RL) has shown promise in training such agents, most of existing approaches typically optimize only for final correctness without considering the efficiency or necessity of external tool use. This often leads to excessive …

trec_web: TREC WT10g (2003)
A web graph network originally constructed in 2003 as a testbed for information-retrieval techniques, including web search engines. Distributed by University of Glasgow.
This network has 1601787 nodes and 8063026 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net…

Zip Bombs: simple, yet powerful in the fight against #AI bots
https://idiallo.com/blog/zipbomb-protection

@… how can I customize search engines in Vivaldi on Android? I don't only want to select from a predefined list, I want to customize the search query string with my own options.

For several years now, every new #Google release has made other search engines, like @… a bit more appealing. I really can't understand why people still keep their emails and stuff there.

trec_web: TREC WT10g (2003)
A web graph network originally constructed in 2003 as a testbed for information-retrieval techniques, including web search engines. Distributed by University of Glasgow.
This network has 1601787 nodes and 8063026 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net…

This was it all along and I didn't find it...
sometimes search engines need to make themselves easier to find!
But I'm glad...
I'm glad that I finally found it...after losing it like 2-3 weeks ago!
https://www.tootfinder.ch/