4 citations · 7 across the 13 of their papers we have counts for
13 papers
Consilience: Conformally Calibrated Communication Control for Hidden-Profile Multi-Agent Reasoning
Abhijith Babu, Ramneet Kaur, Vishal Pramanik +7
Multi-agent LLM systems can improve reasoning by pooling diverse perspectives, but their effectiveness depends on coordinating communication, particularly in hidden-profile setting…
Discovering KV Cache Eviction Policies via LLM-Guided Program Evolution
Pratik Poudel, Yanzhao Wu, Sumit Jha +1
KV cache compression is critical for long-context inference, yet effective eviction policies remain difficult to design: existing prefill-stage methods often rely on hand-crafted s…
Closed-Loop Neural Activation Control in Vision-Language-Action Models
Abhijith Babu, Ramneet Kaur, Nathaniel D. Bastian +5
Vision-Language-Action (VLA) models can be steered at test time by intervening on semantically meaningful internal directions, but existing methods use a fixed steering coefficient…
Exploring Robust Multi-Agent Workflows for Environmental Data Management
Boyuan Guan, Jason Liu, Yanzhao Wu +1
Embedding LLM-driven agents into environmental FAIR data management is compelling - they can externalize operational knowledge and scale curation across heterogeneous data and evol…
GUARD-SLM: Token Activation-Based Defense Against Jailbreak Attacks for Small Language Models
Md Jueal Mia, Joaquin Molto, Yanzhao Wu +1
Small Language Models (SLMs) are emerging as efficient and economically viable alternatives to Large Language Models (LLMs), offering competitive performance with significantly low…
CEQuest: Benchmarking Large Language Models for Construction Estimation
Yanzhao Wu, Lufan Wang, Rui Liu
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of general-domain tasks. However, their effectiveness in specialized fields, such as cons…
Retrieval-Augmented Foundation Models for Water Level Prediction in the Everglades
Rahuul Rangaraj, Jimeng Shi, Rajendra Paudel +2
Accurate water level forecasting in the Everglades is essential for flood mitigation, drought management, water resource planning, and biodiversity conservation. While recent time-…
How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades
Rahuul Rangaraj, Jimeng Shi, Azam Shirali +3
The Everglades play a crucial role in flood and drought regulation, water resource planning, and ecosystem management in the surrounding regions. However, traditional physics-based…
NeRF-APT: A New NeRF Framework for Wireless Channel Prediction
Jingzhou Shen, Tianya Zhao, Yanzhao Wu +1
Neural radiance fields (NeRFs) have recently attracted significant attention in the field of wireless channel prediction, primarily due to their capability for high-fidelity recons…
Deep Learning and Foundation Models for Weather Prediction: A Survey
Jimeng Shi, Azam Shirali, Bowen Jin +10
Physics-based numerical models have been the bedrock of atmospheric sciences for decades, offering robust solutions but often at the cost of significant computational resources. De…
CE-CoLLM: Efficient and Adaptive Large Language Models Through Cloud-Edge Collaboration
Hongpeng Jin, Yanzhao Wu
Large Language Models (LLMs) exhibit remarkable human-like predictive capabilities. However, it is challenging to deploy LLMs to provide efficient and adaptive inference services a…
Boosting Deep Ensembles with Learning Rate Tuning
Hongpeng Jin, Yanzhao Wu
The Learning Rate (LR) has a high impact on deep learning training performance. A common practice is to train a Deep Neural Network (DNN) multiple times with different LR policies…
DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models
Maryam Akhavan Aghdam, Hongpeng Jin, Yanzhao Wu
Transformer-based Mixture-of-Experts (MoE) models have been driving several recent technological advancements in Natural Language Processing (NLP). These MoE models adopt a router…