4 citations · 4 across the 6 of their papers we have counts for
7 papers
Voltic: Distinguishing Volatility from Stochasticity in Recurrent Memory
Parsa Hejabi, Morteza Dehghani, Payam Piray
Recurrent sequence models must decide how strongly to overwrite their memory at each token. Read as Bayesian filtering, this write is the gain of a Kalman update, set by uncertaint…
Realistic threat perception drives intergroup conflict: A causal, dynamic analysis using generative-agent simulations
Suhaib Abdurahman, Farzan Karimi-Malekabadi, Chenxiao Yu +2
Human conflict is often attributed to threats against material conditions and symbolic values, yet it remains unclear how they interact and which dominates. Progress is limited by…
Flip-Flop Consistency: Unsupervised Training for Robustness to Prompt Perturbations in LLMs
Parsa Hejabi, Elnaz Rahmati, Alireza S. Ziabari +1
Large Language Models (LLMs) often produce inconsistent answers when faced with different phrasings of the same prompt. In this paper, we propose Flip-Flop Consistency (), an…
Evaluating Creativity and Deception in Large Language Models: A Simulation Framework for Multi-Agent Balderdash
Parsa Hejabi, Elnaz Rahmati, Alireza S. Ziabari +3
Large Language Models (LLMs) have shown impressive capabilities in complex tasks and interactive environments, yet their creativity remains underexplored. This paper introduces a s…
Cost-Efficient Subjective Task Annotation and Modeling through Few-Shot Annotator Adaptation
Preni Golazizian, Alireza S. Ziabari, Ali Omrani +1
In subjective NLP tasks, where a single ground truth does not exist, the inclusion of diverse annotators becomes crucial as their unique perspectives significantly influence the an…
Community-Informed AI Models for Police Accountability
Benjamin A. T. Graham, Lauren Brown, Georgios Chochlakis +13
Face-to-face interactions between police officers and the public affect both individual well-being and democratic legitimacy. Many government-public interactions are captured on vi…
Towards a Unified Framework for Adaptable Problematic Content Detection via Continual Learning
Ali Omrani, Alireza S. Ziabari, Preni Golazizian +2
Detecting problematic content, such as hate speech, is a multifaceted and ever-changing task, influenced by social dynamics, user populations, diversity of sources, and evolving la…