10 papers
Pseudo-Deliberation in Language Models: When Reasoning Fails to Align Values and Actions
Sushrita Rakshit, Hanwen Zhang, Hua Shen
Large language models (LLMs) are often evaluated based on their stated values, yet these do not reliably translate into their actions, a discrepancy termed "value-action gap." In t…
ValueFlow: Measuring the Propagation of Value Perturbations in Multi-Agent LLM Systems
Jinnuo Liu, Chuke Liu, Hua Shen
Multi-agent large language model (LLM) systems increasingly consist of agents that observe and respond to one another's outputs. While value alignment is typically evaluated for is…
Value Alignment Tax: Measuring Value Trade-offs in LLM Alignment
Jiajun Chen, Hua Shen
Existing work on value alignment typically characterizes value relations statically, ignoring how alignment interventions, such as prompting, fine-tuning, or preference optimizatio…
Bridging Human Interpretation and Machine Representation: A Landscape of Qualitative Data Analysis in the LLM Era
Xinyu Pi, Qisen Yang, Chuong Nguyen +1
LLMs are increasingly used to support qualitative research, yet existing systems produce outputs that vary widely--from trace-faithful summaries to theory-mediated explanations and…
Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI For Reciprocal Human-AI Futures
Hua Shen, Tiffany Knearem, Divy Thakkar +9
The rapid integration of generative AI into everyday life underscores the need to move beyond unidirectional alignment models that only adapt AI to human values. This workshop focu…
ValueCompass: A Framework for Measuring Contextual Value Alignment Between Human and LLMs
Hua Shen, Tiffany Knearem, Reshmi Ghosh +4
As AI systems become more advanced, ensuring their alignment with a diverse range of individuals and societal values becomes increasingly critical. But how can we capture fundament…