Tag Archive for: southern illinois university

Southern Illinois University is a public research university system in Illinois, with its flagship campus in Carbondale founded in 1869 and a major regional campus in Edwardsville. It conducts research across engineering, science, health, and liberal arts and has been designated a high research activity institution under the Carnegie Classification. NECLA and Southern Illinois University collaborate on research in machine learning, optimization, large-scale systems, and trustworthy AI to advance scientific methods and applications. Read our latest publications with Southern Illinois University.

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MARLIN: Multi-Agent Reinforcement Learning for Incremental DAG Discovery

January 27, 2026/in Publications/by NEC Labs America

Uncovering causal structures from observational data is crucial for understanding complex systems and making informed decisions. While reinforcement learning (RL) has shown promise in identifying these structures in the form of a directed acyclic graph (DAG), existing methods often lack efficiency, making them unsuitable for online applications. In this paper, we propose MARLIN, an efficient multi-agent RL-based approach for incremental DAG learning. MARLIN uses a DAG generation policy that maps a continuous real-valued space to the DAG space as an intra-batch strategy, then incorporates two RL agents — state-specific and state-invariant — to uncover causal relationships and integrates these agents into an incremental learning framework. Furthermore, the framework leverages a factored action space to enhance parallelization efficiency. Extensive experiments on synthetic and real datasets demonstrate that MARLIN out-performs state-of-the-art methods in terms of both efficiency and effectiveness.

SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search

December 7, 2025/in Publications/by NEC Labs America

Large Language Models (LLMs) offer promising capabilities for tackling complex reasoning tasks, including optimization problems. However, existing methods either rely on prompt engineering, which leads to poor generalization across problem types, or require costly supervised training. We introduce SolverLLM, a training-free framework that leverages test-time scaling to solve diverse optimization problems. Rather than solving directly, SolverLLM generates mathematical formulations and translates them into solver-ready code, guided by a novel Monte Carlo Tree Search (MCTS) strategy. To enhance the search process, we modify classical MCTS with (1) dynamic expansion for adaptive formulation generation, (2) prompt backpropagation to guide exploration via outcome-driven feedback, and (3) uncertainty backpropagation to incorporate reward reliability into decision-making. Experiments on six standard benchmark datasets demonstrate that SolverLLM outperforms both prompt-based and learning-based baselines, achieving strong generalization without additional training.

NeurIPS 2025 in San Diego from Nov 30th to Dec 5th, 2025

November 19, 2025/in Events/by NEC Labs America

NEC Laboratories America is heading to San Diego for NeurIPS 2025, where our researchers will present cutting-edge work spanning optimization, AI systems, language modeling, and trustworthy machine learning. multi-agent coordination, scalable training, efficient inference, and techniques for detecting LLM-generated text.