6 papers
MoSAIC: Learning DAG Scheduling Heuristics from Optimal Schedules through Motif-Aware Recovery and LLM-Guided Reasoning
Shiva Ahir, Hashmath Shaik, Alex Doboli +2
Efficient task scheduling in heterogeneous computing systems remains a fundamental challenge in embedded and high-level synthesis flows. This paper presents MoSAIC (Motif-aware Sch…
Will the Judge Flip? Predicting Position-Sensitive LLM Judgments from Residual Stream Activations
Hashmath Shaik, Gnaneswar Villuri, Alex Doboli
The order in which candidate responses are presented can change an LLM judge's verdict. Detecting such a position flip ordinarily requires judging each pair in both orders, which d…
The First Token Is Not the Verdict: Hidden Costs of Reading LLM Judges Without Generating
Gnaneswar Villuri, Hashmath Shaik, Alex Doboli
Reading an LLM judge's verdict from the logits of its first generated token is cheap, requires no generation, and is exactly what constrained decoding and likelihood-scoring evalua…
When Do Internal Probes Beat Reading the Answer? Miscalibrated Readouts and Behavior-Concealed Knowledge in Language Models
Gnaneswar Villuri, Hashmath Shaik, Alex Doboli
A 0.6B language model, asked to verify 1,200 logical conclusions (half valid, half corrupted by a single semantic edit), answers YES every time. Judged by behavior it discriminates…
Dynamic Adaptation of the LLM Context for Generating Routines with Coupled Semantics
Gnaneswar Villuri, Hashmath Shaik, Alex Doboli
LLM-based code generation fails when correctness depends on execution-dependent coupling: the meaning of one routine is defined by the runtime behavior of another, a relationship t…
An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems
Hashmath Shaik, Alex Doboli
Large Language Models offer new opportunities to devise automated implementation generation methods that can tackle problem solving activities beyond traditional methods, which req…