[5/5] Persuasion research is still playing catch-up, promising great advancements!β¨
Thank you to my amazing co-authors! @shuhaib.bsky.social @xiaocheng-yang.bsky.social @HyeonjeongHa @ziruicheng.bsky.social @EsinDurmus @JiaxuanYou @HengJi @gokhantur.bsky.social @dilekh.bsky.social
Posts by Beyza Bozdag
[4/5] We'll also be maintaining a GitHub repository for computational persuasion research. Datasets, code, and resources will be included! Contributions and collaborations are warmly welcomed! π
Check it out: github.com/beyzabozdag/...
[3/5] We introduce a taxonomy for computational persuasion research, highlight critical challenges, and map out future directions for safe, fair, and effective persuasive AI systems.
[2/5] We structure computational persuasion around three key perspectives:
π€ AI as Persuader: Generating persuasive content.
π― AI as Persuadee: Vulnerability to persuasive influence.
βοΈ AI as Persuasion Judge: Detecting persuasive tactics and ethical concerns.
Thrilled to announce our new survey that explores the exciting possibilities and troubling risks of computational persuasion in the era of LLMs π€π¬
πArxiv: arxiv.org/pdf/2505.07775
π» GitHub: github.com/beyzabozdag/...
[6/6] Huge thanks to my amazing co-authors @shuhaib.bsky.social, @gokhantur.bsky.social, @dilekh.bsky.social and my lab @convai-uiuc.bsky.social for their help and support! π
Excited to continue exploring LLM persuasiveness & AI safety!
Letβs keep the conversation going! π¬
[5/6] So, who wins the persuasion game? π
π€ Llama-3.3-70B & GPT-4o show similar persuasive effectiveness
π GPT-4o is 50% more resistant to misinformation persuasion vs. Llama-3.3-70B
βοΈ Some models are persuasive, but also too susceptible to persuasion!
[4/6] How does agreement shift over a conversation? π
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Multi-turn persuasion boosts effectivenessβmore chances to influence the Persuadee mean higher agreement over time!
[3/6] We evaluate persuasion across three setups:
π Subjective w/ Single-turn
π Subjective w/ Multi-turn
π Misinformation w/ Multi-turn (β οΈ adversarial!)
π‘ Key finding: Persuasive effectiveness stays fairly stable, but susceptibility varies significantly based on the domain!
[2/6] To assess persuasive effectiveness and susceptibility, we introduce PMIYC β a scalable, automated approach where:
π€ A Persuader tries to convince the other agent
π€ A Persuadee updates its agreement over a multi-turn conversation
Each model debates against the others!π
[1/6] Can LLMs out-persuade each other? π€π§ π¬
Introducing Persuade Me If You Can (PMIYC)βa new framework to evaluate (1) how persuasive LLMs are and (2) how easily they can be persuaded! π
πArxiv: arxiv.org/abs/2503.01829
πProject Page: beyzabozdag.github.io/PMIYC/
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Hi, can I be added as well, thanks!
β I'd like to be added too, thanks!
We had so much fun at #EMNLP2024 during the poster sessions and in Miami ππ Evidence of fun (excursion to the south beach! ποΈ):