5 papers
Compositional Performance Modeling of LLM Inference Clusters with Hierarchical KV Caching
Ruiyang Ma, Sheng Qi, DaiKang Kuang +2
Design-space exploration of LLM inference clusters requires predicting how hardware and serving policies interact with hierarchical key-value (KV) caching. Isolated operation profi…
From Codebase to Culprit (C2C): Reducing the Search Space for Bugs with Semantic Retrieval and Hierarchical Reinforcement Learning
Ankur Garg, Corey Yang-Smith, Rishav Rishav +2
We introduce C2C (From Codebase to Culprit), a framework for precise bug localization that progressively reduces the debugging search space across multiple levels of granularity: f…
Structured Representation Learning with Locally Linear Embeddings and Adaptive Feature Fusion
Somjit Nath, Jackson J Cone, Derek Nowrouzezahrai +1
Neuroscientific research has revealed that the brain encodes complex behaviors by leveraging structured, low-dimensional manifolds and dynamically fusing multiple sources of inform…
The Invisible Hand of Physics: When Video Diffusion Models Know More Than They Show
Parsa Esmati, Somjit Nath, Katja Hofmann +3
Modern video diffusion models generate increasingly realistic and temporally coherent videos, motivating their use as candidate world simulators. Yet it remains unclear whether the…
Discovering Latent Groups for Robust Classification
Ankur Garg, Ulrich Aïvodji, Samira Ebrahimi Kahou +1
Machine learning models exploit spurious correlations, achieving high average accuracy but failing disproportionately on underrepresented subgroups. Existing methods address this b…