collaborators

10 papers

cs.LG2026

Structural Abstraction as an Inductive Bias for Non-Stationary Language Model Training

Elnaz Rahmati, Nona Ghazizadeh, Zhivar Sourati +2

A foundational principle in cognitive science holds that intelligent agents do not learn by storing experiences as isolated instances, but by forming abstract schemas that capture…

cs.CL2026

Tracing Moral Foundations in Large Language Models

Chenxiao Yu, Bowen Yi, Farzan Karimi-Malekabadi +5

Large language models often produce human-like moral judgments, but it is unclear whether this reflects an internal conceptual structure or superficial ``moral mimicry.'' Using Mor…

cs.CL2026

LAD-RAG: Layout-aware Dynamic RAG for Visually-Rich Document Understanding

Zhivar Sourati, Zheng Wang, Marianne Menglin Liu +8

Question answering over visually rich documents (VRDs) requires reasoning not only over isolated content but also over documents' structural organization and cross-page dependencie…

cs.CL2026

The Subjectivity of Respect in Police Traffic Stops: Modeling Community Perspectives in Body-Worn Camera Footage

Preni Golazizian, Elnaz Rahmati, Jackson Trager +17

Traffic stops are among the most frequent police-civilian interactions, and body-worn cameras (BWCs) provide a unique record of how these encounters unfold. Respect is a central di…

cs.LG2026

Personalized Group Relative Policy Optimization for Heterogenous Preference Alignment

Jialu Wang, Heinrich Peters, Asad A. Butt +6

Despite their sophisticated general-purpose capabilities, Large Language Models (LLMs) often fail to align with diverse individual preferences because standard post-training method…

cs.AI2026

Theory Trace Card: Theory-Driven Socio-Cognitive Evaluation of LLMs

Farzan Karimi-Malekabadi, Suhaib Abdurahman, Zhivar Sourati +2

Socio-cognitive benchmarks for large language models (LLMs) often fail to predict real-world behavior, even when models achieve high benchmark scores. Prior work has attributed thi…