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Related papers: Status Hierarchies in Language Models

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Artificial Intelligence (AI) benchmarks play a central role in measuring progress in model development and guiding deployment decisions. However, many benchmarks quickly become saturated, meaning that they can no longer differentiate…

Free-standing social conversations constitute a yet underexplored setting for human behavior forecasting. While the task of predicting pedestrian trajectories has received much recent attention, an intrinsic difference between these…

Machine Learning · Computer Science 2022-08-30 Chirag Raman , Hayley Hung , Marco Loog

When training artificial intelligence (AI) to perform tasks, humans often care not only about whether a task is completed but also how it is performed. As AI agents tackle increasingly complex tasks, aligning their behavior with…

Artificial Intelligence · Computer Science 2026-02-24 Zhiqin Qian , Ryan Diaz , Sangwon Seo , Vaibhav Unhelkar

Amidst the growing interest in developing task-autonomous AI for automated mental health care, this paper addresses the ethical and practical challenges associated with the issue and proposes a structured framework that delineates levels of…

Computers and Society · Computer Science 2024-08-16 Declan Grabb , Max Lamparth , Nina Vasan

People rely on social skills like conflict resolution to communicate effectively and to thrive in both work and personal life. However, practice environments for social skills are typically out of reach for most people. How can we make…

Computation and Language · Computer Science 2024-04-08 Diyi Yang , Caleb Ziems , William Held , Omar Shaikh , Michael S. Bernstein , John Mitchell

Modern language models often exhibit powerful but brittle behavior, leading to the development of larger and more diverse benchmarks to reliably assess their behavior. Here, we suggest that model performance can be benchmarked and…

Computation and Language · Computer Science 2024-02-20 Rajan Vivek , Kawin Ethayarajh , Diyi Yang , Douwe Kiela

English proficiency assessments have become a necessary metric for filtering and selecting prospective candidates for both academia and industry. With the rise in demand for such assessments, it has become increasingly necessary to have the…

Computation and Language · Computer Science 2021-12-01 Pakhi Bamdev , Manraj Singh Grover , Yaman Kumar Singla , Payman Vafaee , Mika Hama , Rajiv Ratn Shah

Learning to communicate through interaction, rather than relying on explicit supervision, is often considered a prerequisite for developing a general AI. We study a setting where two agents engage in playing a referential game and, from…

Machine Learning · Computer Science 2017-11-07 Serhii Havrylov , Ivan Titov

Male-dominated contexts pose a dilemma: they increase the benefits of repeated collaboration among women, yet at the same time, make such collaborations less likely. This paper seeks to understand the conditions that foster repeated…

Computers and Society · Computer Science 2024-07-08 Huimin Xu , Jamie Strassman , Ying Ding , Steven Gray , Maytal Saar-Tsechansky

Small and mid-sized generative language models have gained increasing attention. Their size and availability make them amenable to being analyzed at a behavioral as well as a representational level, allowing investigations of how these…

Machine Learning · Computer Science 2025-04-11 Lorenz Linhardt , Tom Neuhäuser , Lenka Tětková , Oliver Eberle

Game-theoretical models where the rules of the game and the interaction structure both coevolves with the game dynamics -- multiadaptive games -- capture very flexible situations where cooperation among selfish agents can emerge. In this…

Populations and Evolution · Quantitative Biology 2012-10-10 Sungmin Lee , Petter Holme , Zhi-Xi Wu

Large Language Models (LLMs) exhibit surprisingly diverse risk preferences when acting as AI decision makers, a crucial characteristic whose origins remain poorly understood despite their expanding economic roles. We analyze 50 LLMs using…

General Economics · Economics 2025-06-11 Shumiao Ouyang , Hayong Yun , Xingjian Zheng

An implicit expectation of asking users to rate agents, such as an AI decision-aid, is that they will use only relevant information -- ask them about an agent's benevolence, and they should consider whether or not it was kind. Behavioral…

Human-Computer Interaction · Computer Science 2023-07-28 Nikolos Gurney , David Pynadath , Ning Wang

Envy shapes competitiveness and cooperation in human groups, yet its role in large language model interactions remains largely unexplored. As LLMs increasingly operate in multi-agent settings, it is important to examine whether they exhibit…

Can large language model (LLM) agents reproduce the complex social dynamics that characterize human online behavior -- shaped by homophily, reciprocity, and social validation -- and what memory and learning mechanisms enable such dynamics…

Artificial Intelligence · Computer Science 2025-10-23 Philipp J. Schneider , Lin Tian , Marian-Andrei Rizoiu

End-to-end models for goal-orientated dialogue are challenging to train, because linguistic and strategic aspects are entangled in latent state vectors. We introduce an approach to learning representations of messages in dialogues by…

Computation and Language · Computer Science 2018-06-06 Denis Yarats , Mike Lewis

Documents are composed of smaller pieces - paragraphs, sentences, and tokens - that have complex relationships between one another. Sentiment classification models that take into account the structure inherent in these documents have a…

Computation and Language · Computer Science 2022-02-03 Jeremy Barnes , Vinit Ravishankar , Lilja Øvrelid , Erik Velldal

One of the fundamental quests of AI is to produce agents that coordinate well with humans. This problem is challenging, especially in domains that lack high quality human behavioral data, because multi-agent reinforcement learning (RL)…

Artificial Intelligence · Computer Science 2023-06-13 Hengyuan Hu , Dorsa Sadigh

Large language models, comprising billions of parameters and pre-trained on extensive web-scale corpora, have been claimed to acquire certain capabilities without having been specifically trained on them. These capabilities, referred to as…

Computation and Language · Computer Science 2024-07-16 Sheng Lu , Irina Bigoulaeva , Rachneet Sachdeva , Harish Tayyar Madabushi , Iryna Gurevych

Modern Reinforcement Learning (RL) algorithms are able to outperform humans in a wide variety of tasks. Multi-agent reinforcement learning (MARL) settings present additional challenges, and successful cooperation in mixed-motive groups of…

Multiagent Systems · Computer Science 2024-06-25 Ram Rachum , Yonatan Nakar , Bill Tomlinson , Nitay Alon , Reuth Mirsky