3 citations · 5 across the 2 of their papers we have counts for
4 papers · 1 filter
RAudit: A Blind Auditing Protocol for Large Language Model Reasoning
Edward Y. Chang, Longling Geng
Inference-time scaling can amplify reasoning pathologies: sycophancy, rung collapse, and premature certainty. We present RAudit, a diagnostic protocol for auditing LLM reasoning wi…
ALAS: A Stateful Multi-LLM Agent Framework for Disruption-Aware Planning
Edward Y. Chang, Longling Geng
Large language models (LLMs) excel at rapid generation of text and multimodal content, yet they falter on transaction-style planning that demands ACID-like guarantees and real-time…
SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning
Edward Y. Chang, Longling Geng
This paper introduces SagaLLM, a structured multi-agent architecture designed to address four foundational limitations of current LLM-based planning systems: unreliable self-valida…
REALM-Bench: A Benchmark for Evaluating Multi-Agent Systems on Real-world, Dynamic Planning and Scheduling Tasks
Longling Geng, Edward Y. Chang
This benchmark suite provides a comprehensive evaluation framework for assessing both individual LLMs and multi-agent systems in Real-world planning and scheduling scenarios. The s…