Tootfinder

Youth Privacy in Australia: Insights from National Policy Dialogues
https://fpf.org/blog/youth-privacy-in-australia-insights-from-national-policy-dialogues/
@…

Popcorn Dialogues: A Popculture Podcast
Take a deep dive into great movies, television and all things entertainment...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/popcorn-dialogues/

SafeMT: Multi-turn Safety for Multimodal Language Models
Han Zhu, Juntao Dai, Jiaming Ji, Haoran Li, Chengkun Cai, Pengcheng Wen, Chi-Min Chan, Boyuan Chen, Yaodong Yang, Sirui Han, Yike Guo
https://arxiv.org/abs/2510.12133

SafeMT: Multi-turn Safety for Multimodal Language Models
With the widespread use of multi-modal Large Language models (MLLMs), safety issues have become a growing concern. Multi-turn dialogues, which are more common in everyday interactions, pose a greater risk than single prompts; however, existing benchmarks do not adequately consider this situation. To encourage the community to focus on the safety issues of these models in multi-turn dialogues, we introduce SafeMT, a benchmark that features dialogues of varying lengths generated from harmful quer…

Theoretical Inquiries, Critical Dialogues I–II (April 2026 & April 2027) https://call-for-papers.sas.upenn.edu/cfp/2025/12/08/theoretical-inquiries-critical-dialogues-i–ii-april-2026-april-2027<…

Dialogues with AI Reduce Beliefs in Misinformation but Build No Lasting Discernment Skills
Anku Rani, Valdemar Danry, Paul Pu Liang, Andrew B. Lippman, Pattie Maes
https://arxiv.org/abs/2510.01537

Dialogues with AI Reduce Beliefs in Misinformation but Build No Lasting Discernment Skills
Given the growing prevalence of fake information, including increasingly realistic AI-generated news, there is an urgent need to train people to better evaluate and detect misinformation. While interactions with AI have been shown to durably reduce people's beliefs in false information, it is unclear whether these interactions also teach people the skills to discern false information themselves. We conducted a month-long study where 67 participants classified news headline-image pairs as real o…

Lin, H., Czarnek, G., Lewis, B. et al.
Persuading voters using human–artificial intelligence dialogues.
Nature (2025). https://doi.org/10.1038/s41586-025-09771-9

MedKGEval: A Knowledge Graph-Based Multi-Turn Evaluation Framework for Open-Ended Patient Interactions with Clinical LLMs
Yuechun Yu, Han Ying, Haoan Jin, Wenjian Jiang, Dong Xian, Binghao Wang, Zhou Yang, Mengyue Wu
https://arxiv.org/abs/2510.12224

MedKGEval: A Knowledge Graph-Based Multi-Turn Evaluation Framework for Open-Ended Patient Interactions with Clinical LLMs
The reliable evaluation of large language models (LLMs) in medical applications remains an open challenge, particularly in capturing the complexity of multi-turn doctor-patient interactions that unfold in real clinical environments. Existing evaluation methods typically rely on post hoc review of full conversation transcripts, thereby neglecting the dynamic, context-sensitive nature of medical dialogues and the evolving informational needs of patients. In this work, we present MedKGEval, a nove…

Challenge: "Name 20 female authors you admire, 1 per day"
Day 14:
Anne Donovan
Her novel "BuddhaDa" is one of the most clever, hilarious, uplifting and yet very serious works of literature I've ever read. It sits on my favourites shelf. As she writes the dialogues the way people talk, you will learn some Scots Glasgow dialect along the way. I had the pleasure of attending a reading with her at a local library in Edinburgh and she signed this much-love…

Replaced article(s) found for cs.CY. https://arxiv.org/list/cs.CY/new
[1/1]:
- Simulating Persuasive Dialogues on Meat Reduction with Generative Agents
Georg Ahnert, Elena Wurth, Markus Strohmaier, Jutta Mata

Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards
Yiran Shen, Yu Xia, Jonathan Chang, Prithviraj Ammanabrolu
https://arxiv.org/abs/2510.01167 h…

Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards
Aligning large language models to human preferences is inherently multidimensional, yet most pipelines collapse heterogeneous signals into a single optimizeable objective. We seek to answer what it would take to simultaneously align a model across various domains spanning those with: verifiable rewards (mathematical accuracy), non-verifiable subjective preferences (human values), and complex interactive scenarios (multi-turn AI tutoring dialogues). Such multi-objective reinforcement learning se…

Christian–Muslim Encounters and Dialogues over the Centuries: The Christian–Muslim Relationship for Bringing Peace and Harmony
https://ift.tt/yxqtuFY
updated: Thursday, December 18, 2025 - 10:58pmfull name / name of organization: MDPI, Religions…
via Input 4 RELCFP

Beyond Words: Infusing Conversational Agents with Human-like Typing Behaviors
Jijie Zhou, Yuhan Hu
https://arxiv.org/abs/2510.08912 https://arxiv.org/pdf/2…

Beyond Words: Infusing Conversational Agents with Human-like Typing Behaviors
Recently, large language models have facilitated the emergence of highly intelligent conversational AI capable of engaging in human-like dialogues. However, a notable distinction lies in the fact that these AI models predominantly generate responses rapidly, often producing extensive content without emulating the thoughtful process characteristic of human cognition and typing. This paper presents a design aimed at simulating human-like typing behaviors, including patterns such as hesitation and…

Time-To-Inconsistency: A Survival Analysis of Large Language Model Robustness to Adversarial Attacks
Yubo Li, Ramayya Krishnan, Rema Padman
https://arxiv.org/abs/2510.02712 http…

Time-To-Inconsistency: A Survival Analysis of Large Language Model Robustness to Adversarial Attacks
Large Language Models (LLMs) have revolutionized conversational AI, yet their robustness in extended multi-turn dialogues remains poorly understood. Existing evaluation frameworks focus on static benchmarks and single-turn assessments, failing to capture the temporal dynamics of conversational degradation that characterize real-world interactions. In this work, we present the first comprehensive survival analysis of conversational AI robustness, analyzing 36,951 conversation turns across 9 stat…

Synthetic Dialogue Generation for Interactive Conversational Elicitation & Recommendation (ICER)
Moonkyung Ryu, Chih-Wei Hsu, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
https://arxiv.org/abs/2510.02331

Synthetic Dialogue Generation for Interactive Conversational Elicitation & Recommendation (ICER)
While language models (LMs) offer great potential for conversational recommender systems (CRSs), the paucity of public CRS data makes fine-tuning LMs for CRSs challenging. In response, LMs as user simulators qua data generators can be used to train LM-based CRSs, but often lack behavioral consistency, generating utterance sequences inconsistent with those of any real user. To address this, we develop a methodology for generating natural dialogues that are consistent with a user's underlying sta…

Theoretical Inquiries, Critical Dialogues I–II (April 2026 & April 2027)
https://ift.tt/AKqULBt
updated: Monday, December 8, 2025 - 1:09pmfull name / name of organization: Nesir: Journal of…
via Input 4 RELCFP …

MDSEval: A Meta-Evaluation Benchmark for Multimodal Dialogue Summarization
Yinhong Liu, Jianfeng He, Hang Su, Ruixue Lian, Yi Nian, Jake Vincent, Srikanth Vishnubhotla, Robinson Piramuthu, Saab Mansour
https://arxiv.org/abs/2510.01659

MDSEval: A Meta-Evaluation Benchmark for Multimodal Dialogue Summarization
Multimodal Dialogue Summarization (MDS) is a critical task with wide-ranging applications. To support the development of effective MDS models, robust automatic evaluation methods are essential for reducing both cost and human effort. However, such methods require a strong meta-evaluation benchmark grounded in human annotations. In this work, we introduce MDSEval, the first meta-evaluation benchmark for MDS, consisting image-sharing dialogues, corresponding summaries, and human judgments across …