Buchumschlag

Greater than the sum of its parts: The role of minority and majority status in collaborative problem-solving communication

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Cavazos, Jacqueline G., Nixon, Nia
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Computation and Language
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Measuring Inclusion in Interaction: Inclusion Analytics for Human-AI Collaborative Learning
von: Choi, Jaeyoon, et al.
Veröffentlicht: (2026)

Trusting CHATGPT: how minor tweaks in the prompts lead to major differences in sentiment classification
von: Cuellar, Jaime E., et al.
Veröffentlicht: (2025)

Tree of Problems: Improving structured problem solving with compositionality
von: Zebaze, Armel, et al.
Veröffentlicht: (2024)

A self-evolving multi-role collaborative framework with fine-grained difficulty guidance for innovative mathematical problem generation
von: Sun, Yifei, et al.
Veröffentlicht: (2026)

Which symbol grounding problem should we try to solve?
von: Müller, Vincent C.
Veröffentlicht: (2025)

With Greater Text Comes Greater Necessity: Inference-Time Training Helps Long Text Generation
von: Wang, Y., et al.
Veröffentlicht: (2024)

Greater accessibility can amplify discrimination in generative AI
von: Holtermann, Carolin, et al.
Veröffentlicht: (2026)

Functional Subspace, where language models can use vector algebra to solve problems
von: Lee, Jung H., et al.
Veröffentlicht: (2026)

On Ambiguity: The case of fraction, its meanings and roles
von: Bergstra, Jan A, et al.
Veröffentlicht: (2026)

Catalyzing Equity in STEM Teams: Harnessing Generative AI for Inclusion and Diversity
von: Nixon, Nia, et al.
Veröffentlicht: (2024)

Give me a hint: Can LLMs take a hint to solve math problems?
von: Agrawal, Vansh, et al.
Veröffentlicht: (2024)

Human Languages with Greater Information Density Increase Communication Speed, but Decrease Conversation Breadth
von: Aceves, Pedro, et al.
Veröffentlicht: (2021)

When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full Models
von: Chang, Ting-Yun, et al.
Veröffentlicht: (2024)

AdpQ: A Zero-shot Calibration Free Adaptive Post Training Quantization Method for LLMs
von: Ghaffari, Alireza, et al.
Veröffentlicht: (2024)

Personalities at Play: Probing Alignment in AI Teammates
von: Samadi, Mohammad Amin, et al.
Veröffentlicht: (2026)

Structure-Learnable Adapter Fine-Tuning for Parameter-Efficient Large Language Models
von: Gong, Ming, et al.
Veröffentlicht: (2025)

Is Programming by Example solved by LLMs?
von: Li, Wen-Ding, et al.
Veröffentlicht: (2024)

Pause and Reflect: Conformal Aggregation for Chain-of-Thought Reasoning
von: Gu, Yu, et al.
Veröffentlicht: (2026)

The role of generative AI in collaborative problem‐solving of authentic challenges
von: Nancy Law, et al.
Veröffentlicht: (2025)

Transforming Dental Diagnostics with Artificial Intelligence: Advanced Integration of ChatGPT and Large Language Models for Patient Care
von: Nia, Masoumeh Farhadi, et al.
Veröffentlicht: (2024)

A foundation model for human-AI collaboration in medical literature mining
von: Wang, Zifeng, et al.
Veröffentlicht: (2025)

AI in Mental Health: Emotional and Sentiment Analysis of Large Language Models' Responses to Depression, Anxiety, and Stress Queries
von: VarastehNezhad, Arya, et al.
Veröffentlicht: (2025)

MaterialFigBENCH: benchmark dataset with figures for evaluating college-level materials science problem-solving abilities of multimodal large language models
von: Yoshitake, Michiko, et al.
Veröffentlicht: (2026)

Intercultural communication: a fundamental tool for relationships and human behaviour in international collaboration
von: Juana Idania Pérez Morales
Veröffentlicht: (2021)

Mitigating Outlier Activations in Low-Precision Fine-Tuning of Language Models
von: Ghaffari, Alireza, et al.
Veröffentlicht: (2023)

Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models
von: Tian, Changxin, et al.
Veröffentlicht: (2025)

Learning and communication pressures in neural networks: Lessons from emergent communication
von: Galke, Lukas, et al.
Veröffentlicht: (2024)

Are Large Language Models More Empathetic than Humans?
von: Welivita, Anuradha, et al.
Veröffentlicht: (2024)

DAWN-ICL: Strategic Planning of Problem-solving Trajectories for Zero-Shot In-Context Learning
von: Tang, Xinyu, et al.
Veröffentlicht: (2024)

MANBench: Is Your Multimodal Model Smarter than Human?
von: Zhou, Han, et al.
Veröffentlicht: (2025)

The expected sum of edge lengths in planar linearizations of trees. Theory and applications
von: Alemany-Puig, Lluís, et al.
Veröffentlicht: (2022)

Pragmatics beyond humans: meaning, communication, and LLMs
von: Gvoždiak, Vít
Veröffentlicht: (2025)

Word reuse and combination support efficient communication of emerging concepts
von: Xu, Aotao, et al.
Veröffentlicht: (2024)

Ask the experts: sourcing high-quality datasets for nutritional counselling through Human-AI collaboration
von: Balloccu, Simone, et al.
Veröffentlicht: (2024)

Entity-Level Sentiment: More than the Sum of Its Parts
von: Rønningstad, Egil, et al.
Veröffentlicht: (2024)

Meta-Learning Neural Mechanisms rather than Bayesian Priors
von: Goodale, Michael, et al.
Veröffentlicht: (2025)

LLMs Know More About Numbers than They Can Say
von: Yuchi, Fengting, et al.
Veröffentlicht: (2026)

The Knowledge Microscope: Features as Better Analytical Lenses than Neurons
von: Chen, Yuheng, et al.
Veröffentlicht: (2025)

Automated Coding of Communications in Collaborative Problem-solving Tasks Using ChatGPT
von: Hao, Jiangang, et al.
Veröffentlicht: (2024)

Modelling prospective memory and resilient situated communications via Wizard of Oz
von: Li, Yanzhe, et al.
Veröffentlicht: (2023)