2 citations · 2 across the 6 of their papers we have counts for
6 papers
Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
Mohammad Ali Alomrani, Yingxue Zhang, Derek Li +14
Large language models (LLMs) have rapidly progressed into general-purpose agents capable of solving a broad spectrum of tasks. However, current models remain inefficient at reasoni…
Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation
Lingfeng Zhang, Yuecheng Liu, Zhanguang Zhang +19
Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, enabling agents to leverage commonsense…
MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization
Faezeh Faez, Raika Karimi, Yingxue Zhang +4
Electronic Design Automation (EDA) is essential for IC design and has recently benefited from AI-based techniques to improve efficiency. Logic synthesis, a key EDA stage, transform…
Logic Synthesis Optimization with Predictive Self-Supervision via Causal Transformers
Raika Karimi, Faezeh Faez, Yingxue Zhang +4
Contemporary hardware design benefits from the abstraction provided by high-level logic gates, streamlining the implementation of logic circuits. Logic Synthesis Optimization (LSO)…
Scalable Graph Self-Supervised Learning
Ali Saheb Pasand, Reza Moravej, Mahdi Biparva +2
In regularization Self-Supervised Learning (SSL) methods for graphs, computational complexity increases with the number of nodes in graphs and embedding dimensions. To mitigate the…
Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization
Mahdi Biparva, Raika Karimi, Faezeh Faez +1
Temporal Graph Neural Networks have garnered substantial attention for their capacity to model evolving structural and temporal patterns while exhibiting impressive performance. Ho…