NeurIPS 2024PastOther
NeurIPS 2024 Workshop on Behavioral Machine Learning
NeurIPS 2024 Workshop on Behavioral ML
- Submission deadline
- Sep 17, 2024, 00:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (72)
Fetched from OpenReview (v2) on 2026-06-10.
A Behavioral Economics Approach to Principled Multi-Agent Reinforcement Learning
A New Approach to Generate Individual Level Data of Walled Garden Platforms: Linear Programming Reconstruction
A Spatio-Temporal Flow Matching Framework for Pedestrian Trajectory Prediction
Accuracy Isn’t Everything: Understanding the Desiderata of AI Tools in Legal-Financial Settings
An Experimental Study of Competitive Market Behavior Through LLMs
Analyzing Reward Functions via Trajectory Alignment
Are LLMs good pragmatic speakers?
Assessing Behavioral Alignment of Personality-Driven Generative Agents in Social Dilemma Games
Assessing Social Alignment: Do Personality-Prompted Large Language Models Behave Like Humans?
Attention Redistribution During Event Segmentation In Large Language Model
Behavioral Sequence Modeling with Ensemble Learning
Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks
Cognitive Bias for Human-AI ad hoc Teamwork
Comparing Human and LLM Ratings of Music-Recommendation Quality with User Context
Computational discovery of human reinforcement learning dynamics from choice behavior
CoS: Enhancing Personalization with Context Steering
Debiasing Global Workspace: A Cognitive Neural Framework for Learning Debiased and Interpretable Representations
Deep and shallow thinking in a single forward pass
Designing Algorithmic Delegates
Do Language Models Have Bayesian Brains? Distinguishing Stochastic and Deterministic Decision Patterns within Large Language Models
Does GPT Really Get It? A Hierarchical Scale to Quantify Human and AI's Understanding of Algorithms
Empowering Neural Networks with Control and Planning Abilities
Evidence from the Synthetic Laboratory: Language Models as Auction Participants
ExpressivityArena: Can LLMs Express Information Implicitly?
From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs
Generating and Validating Agent and Environment Code for Simulating Realistic Personality Profiles with Large Language Models
Helping People Predict Agent Behaviors by Operationalizing the Variation Theory of Learning
HuLE-Nav: Human-Like Exploration for Zero-Shot Object Navigation via Vision-Language Models
Impact of a biomimetic training regimen based on early visual experience on neural network organization and behavior
Improving optimal control and estimation for realistic noise models of the sensorimotor system
Integrating Preference-Aware Modeling of Human Spatial Behavior in Cyber-Physical-Human Systems
Investigating Same-Different Concept Understanding in Generative Multimodal Models
Learning to Cooperate with Humans using Generative Agents
Limitations in Planning Ability in AlphaZero
LLM to Bridge Human Instructions with a Dynamic Symbolic Representation in Hierarchical Reinforcement Learning
LLMs and Personalities: Inconsistencies Across Scales
Meaning Through Motion: DUET – A Multimodal Dataset for Kinesics Analysis in Dyadic Activities
Measuring Implicit Bias in Explicitly Unbiased Large Language Models
Mitigating Overconfidence in Large Language Models: A Behavioral Lens on Confidence Estimation and Calibration
Modulating Language Model Experiences through Frictions
Monitoring Behavioral Changes Using Spatiotemporal Graphs: A Case Study on the StudentLife Dataset
Multimodal Integration in Audio-Visual Speech Recognition --- How Far Are We From Human-Level Robustness?
Multivariate Prediction of Human Behavior in Task fMRI
MuMA-ToM: Multi-modal Multi-Agent Theory of Mind
Non-local Exchange: Introduce Non-locality via Graph Re-wiring to Graph Neural Networks
Optimizing Reward Models with Proximal Policy Exploration in Preference-Based Reinforcement Learning
Outcome-Irrelevant and State-Independent Learning Mechanisms in Human Reinforcement Learning
PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
Predicting human decisions with behavioral theories and machine learning
Principled probing of foundation models in the auditory modality
Principles of Animal Cognition for LLM Evaluations: A Case Study on Transitive Inference
Probing LLM World Models: Enhancing Guesstimation with Wisdom of Crowds Decoding
pSAE-chiatry: Utilizing Sparse Autoencoders to Uncover Mental-Health-Related Features in Language Models
Rational Metareasoning for Large Language Models
Reassessing Number-Detector Units in Convolutional Neural Networks
Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors
Selective Preference Aggregation
Self-Attention Limits Working Memory Capacity of Transformer-Based Models
StepCountJITAI: simulation environment for RL with application to physical activity adaptive intervention
Superficial Alignment, Subtle Divergence, and Nudge Sensitivity in LLM Decision-Making
The Double-Edged Sword of Behavioral Responses in Strategic Classification
Towards Deliberating Agents: Evaluating the Ability of Large Language Models to Deliberate
Towards Robust Estimation of Human Intention Hierarchy in Robot Teleoperation
Ultimatum Bargaining: Algorithms vs. Humans
Understanding Graphical Perception in Data Visualization through Zero-shot Prompting of Vision-Language Models
Unexploited Information Value in Human-AI Collaboration
Using LLMs to Model the Beliefs and Preferences of Targeted Populations
Virtual Personas for Language Models via an Anthology of Backstories
Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
What you say or how you say it? Predicting Conflict Outcomes in Real and LLM-Generated Conversations
WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback
Words that work: Using language to generate hypotheses