1 citations · 1 across the 7 of their papers we have counts for
8 papers
R2V Agent: Teaching SLMs When to Ask for Help
Raghu Vamshi Hemadri, Humaira Firdowse Mohammed, Rishabh Maheshwary +5
Efficient agentic systems should incur expensive frontier-model costs only on decisions where a cheaper local model is likely to fail. Existing LLM cascades usually route whole que…
TrojanLoC: LLM-based Framework for RTL Trojan Localization
Weihua Xiao, Zeng Wang, Minghao Shao +6
Hardware Trojans (HT s) are a persistent threat to integrated circuits, especially when inserted at the register-transfer level (RTL). Existing methods typically first convert the…
VeriDispatcher: Multi-Model Dispatching through Pre-Inference Difficulty Prediction for RTL Generation Optimization
Zeng Wang, Weihua Xiao, Minghao Shao +4
Large Language Models (LLMs) show strong performance in RTL generation, but different models excel on different tasks because of architecture and training differences. Prior work m…
OncoReason: Structuring Clinical Reasoning in LLMs for Robust and Interpretable Survival Prediction
Raghu Vamshi Hemadri, Geetha Krishna Guruju, Kristi Topollai +1
Predicting cancer treatment outcomes requires models that are both accurate and interpretable, particularly in the presence of heterogeneous clinical data. While large language mod…
VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code
Raghu Vamshi Hemadri, Jitendra Bhandari, Andre Nakkab +5
Modern chip design is complex, and there is a crucial need for early-stage prediction of key design-quality metrics like timing and routing congestion directly from Verilog code (a…
PrefixLLM: LLM-aided Prefix Circuit Design
Weihua Xiao, Venkata Sai Charan Putrevu, Raghu Vamshi Hemadri +2
Prefix circuits are fundamental components in digital adders, widely used in digital systems due to their efficiency in calculating carry signals. Synthesizing prefix circuits with…