7 papers
Lattice Boltzmann Method for Compressible Navier-Stokes-Fourier Equations
Fedor Bukreev, Adrian Kummerländer, Mathias J. Krause
A lattice Boltzmann scheme for the three-dimensional compressible Navier--Stokes--Fourier equations, derived automatically from the declared system by a symbolic compiler, is valid…
CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models
Zixuan Liu, Juntao Cai, Xiaoxu Cai +2
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in multimodal understanding and generation. However, when textual inputs conflict with visual evi…
MemBoost: A Memory-Boosted Framework for Cost-Aware LLM Inference
Joris Köster, Zixuan Liu, Siavash Khajavi +1
Large Language Models (LLMs) deliver strong performance but incur high inference cost in real-world services, especially under workloads with repeated or near-duplicate queries acr…
LycheeCluster: Efficient Long-Context Inference with Structure-Aware Chunking and Hierarchical KV Indexing
Dongfang Li, Zixuan Liu, Gang Lin +2
The quadratic complexity of the attention mechanism and the substantial memory footprint of the Key-Value (KV) cache present severe computational and memory challenges for Large La…
Targeting Misalignment: A Conflict-Aware Framework for Reward-Model-based LLM Alignment
Zixuan Liu, Siavash H. Khajavi, Guangkai Jiang +1
Reward-model-based fine-tuning is a central paradigm in aligning Large Language Models with human preferences. However, such approaches critically rely on the assumption that proxy…
DetectiumFire: A Comprehensive Multi-modal Dataset Bridging Vision and Language for Fire Understanding
Zixuan Liu, Siavash H. Khajavi, Guangkai Jiang
Recent advances in multi-modal models have demonstrated strong performance in tasks such as image generation and reasoning. However, applying these models to the fire domain remain…