Tootfinder

Consistent Explainers or Unreliable Narrators? Understanding LLM-generated Group Recommendations
Cedric Waterschoot, Nava Tintarev, Francesco Barile
https://arxiv.org/abs/2507.13705

Consistent Explainers or Unreliable Narrators? Understanding LLM-generated Group Recommendations
Large Language Models (LLMs) are increasingly being implemented as joint decision-makers and explanation generators for Group Recommender Systems (GRS). In this paper, we evaluate these recommendations and explanations by comparing them to social choice-based aggregation strategies. Our results indicate that LLM-generated recommendations often resembled those produced by Additive Utilitarian (ADD) aggregation. However, the explanations typically referred to averaging ratings (resembling but not…

FDA significantly limits COVID-19 vaccine recommendations. Well, #COVID19 IS gone! Isn't it??
https://www.cidrap.umn.edu/covid-19/fda-significantly-limits-covid-19-vaccine-recommendations

Lions' David Montgomery says 2025 is a 'year of reckoning' as Detroit aims to finally break through

https://www.cbssports.com/nfl/news/lions-d

Point of Interest Recommendation: Pitfalls and Viable Solutions
Alejandro Bellog\'in, Linus W. Dietz, Francesco Ricci, Pablo S\'anchez
https://arxiv.org/abs/2507.13725

Point of Interest Recommendation: Pitfalls and Viable Solutions
Point of interest (POI) recommendation can play a pivotal role in enriching tourists' experiences by suggesting context-dependent and preference-matching locations and activities, such as restaurants, landmarks, itineraries, and cultural attractions. Unlike some more common recommendation domains (e.g., music and video), POI recommendation is inherently high-stakes: users invest significant time, money, and effort to search, choose, and consume these suggested POIs. Despite the numerous researc…

I was outside today sitting in the shade reading this. I'd read it years ago but it was very enjoyable reading it again. I really recommend it! Bonus if you like watches, science or a story of one man's pursuit of perfection.
[Low quality picture as I left my smartphone behind and only had a Nokia 225 4G feature phone with me. Something else I recommend!]

Pakistan to nominate Donald Trump for Nobel peace prize (Associated Press)
https://www.theguardian.com/us-news/2025/jun/21/pakistan-trump-nobel-prize-recommendation-india-ceasefire
http://www.memeorandum.com/250621/p26#a250621p26

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers
Tommaso Green, Martin Gubri, Haritz Puerto, Sangdoo Yun, Seong Joon Oh
https://arxiv.org/abs/2506.15674

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers
We study privacy leakage in the reasoning traces of large reasoning models used as personal agents. Unlike final outputs, reasoning traces are often assumed to be internal and safe. We challenge this assumption by showing that reasoning traces frequently contain sensitive user data, which can be extracted via prompt injections or accidentally leak into outputs. Through probing and agentic evaluations, we demonstrate that test-time compute approaches, particularly increased reasoning steps, ampl…

Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
Genki Kusano, Kosuke Akimoto, Kunihiro Takeoka
https://arxiv.org/abs/2507.13525

Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
Large language models (LLMs) can perform recommendation tasks by taking prompts written in natural language as input. Compared to traditional methods such as collaborative filtering, LLM-based recommendation offers advantages in handling cold-start, cross-domain, and zero-shot scenarios, as well as supporting flexible input formats and generating explanations of user behavior. In this paper, we focus on a single-user setting, where no information from other users is used. This setting is practi…

Collaborative Rational Speech Act: Pragmatic Reasoning for Multi-Turn Dialog
Lautaro Estienne, Gabriel Ben Zenou, Nona Naderi, Jackie Cheung, Pablo Piantanida
https://arxiv.org/abs/2507.14063

Collaborative Rational Speech Act: Pragmatic Reasoning for Multi-Turn Dialog
As AI systems take on collaborative roles, they must reason about shared goals and beliefs-not just generate fluent language. The Rational Speech Act (RSA) framework offers a principled approach to pragmatic reasoning, but existing extensions face challenges in scaling to multi-turn, collaborative scenarios. In this paper, we introduce Collaborative Rational Speech Act (CRSA), an information-theoretic (IT) extension of RSA that models multi-turn dialog by optimizing a gain function adapted from…

DUALRec: A Hybrid Sequential and Language Model Framework for Context-Aware Movie Recommendation
Yitong Li, Raoul Grasman
https://arxiv.org/abs/2507.13957 …

DUALRec: A Hybrid Sequential and Language Model Framework for Context-Aware Movie Recommendation
The modern recommender systems are facing an increasing challenge of modelling and predicting the dynamic and context-rich user preferences. Traditional collaborative filtering and content-based methods often struggle to capture the temporal patternings and evolving user intentions. While Large Language Models (LLMs) have gained gradual attention in recent years, by their strong semantic understanding and reasoning abilities, they are not inherently designed to model chronologically evolving us…