3 papers
cs.LG2026
TraceNAS: Zero-shot LLM Pruning via Gradient Trace Correlation
Prajna G. Malettira, Manish Nagaraj, Arjun Roy +2
Structured pruning is essential for efficient deployment of Large Language Models (LLMs). The varying sensitivity of LLM sub-blocks to pruning necessitates the identification of op…
cs.LG2026
TopoPrune: Robust Data Pruning via Unified Latent Space Topology
Arjun Roy, Prajna G. Malettira, Manish Nagaraj +1
Geometric data pruning methods, while practical for leveraging pretrained models, are fundamentally unstable. Their reliance on extrinsic geometry renders them highly sensitive to…
cs.NE2024
TSkips: Efficiency Through Explicit Temporal Delay Connections in Spiking Neural Networks
Prajna G. Malettira, Shubham Negi, Wachirawit Ponghiran +1
Spiking Neural Networks (SNNs) with their bio-inspired Leaky Integrate-and-Fire (LIF) neurons inherently capture temporal information. This makes them well-suited for sequential ta…