collaborators

6 papers

cs.LG2026

ChipMEM: Verification-Grounded Memory for EDA Agents

Abdulrahman AlRabah, Joshua Mabry, Dilek Hakkani-Tür +4

Large language model (LLM)-based agents use Electronic Design Automation (EDA) tools to generate and revise register-transfer-level (RTL) designs under synthesis and verification f…

cs.CL2026

From SQL Errors to Concept Gaps: An AI-Powered Knowledge Graph Analytics Platform for Personalized Feedback

Abdulrahman AlRabah, Weijian Zhou, Xing Gao +1

This innovative practice full paper describes an AI-powered knowledge graph platform that connects SQL errors to conceptual gaps in undergraduate and graduate database systems cour…

cs.CL2026

PredAct-Bench: Benchmarking Tool-Augmented Dialogue under Controlled Tool Noise

Abdulrahman AlRabah, Xiaocheng Yang, Dilek Hakkani-Tür +1

Large Language Models (LLMs) are increasingly deployed in task-oriented dialogue systems that support multi-step decision-making in high-stakes domains such as education, healthcar…

cs.MA2026

GBC: Gradient-Based Connections for Optimizing Multi-Agent Systems

Xiaocheng Yang, Abdulrahman Alrabah, Dilek Hakkani-Tür +1

Multi-agent systems (MAS) built on large language models (LLMs) provide a promising framework for solving complex tasks through role specialization and structured interaction. Howe…

cs.CL2026

Too Polite to Disagree: Understanding Sycophancy Propagation in Multi-Agent Systems

Vira Kasprova, Amruta Parulekar, Abdulrahman AlRabah +5

Large language models (LLMs) often exhibit sycophancy: agreement with user stance even when it conflicts with the model's opinion. While prior work has mostly studied this in singl…

cs.AI2026

Instructor-Aligned Knowledge Graphs for Personalized Learning

Abdulrahman AlRabah, Priyanka Kargupta, Jiawei Han +1

Mastering educational concepts requires understanding both their prerequisites (e.g., recursion before merge sort) and sub-concepts (e.g., merge sort as part of sorting algorithms)…