14 citations · 47 across the 14 of their papers we have counts for
7 papers · 1 filter
PRIME: Towards Verifiable Evidence-Grounded Reasoning in LLM Agents
Hamed Khosravi, Xiaoming Huo
LLM agents are used to check records against an organization's requirements, for example whether a vulnerability report is ready for investigation. Requirements often allow several…
Certified Corruption Budgets: Anytime-Valid Leaderboard Claims under Adaptive Rigging
Hamed Khosravi, Xiaoming Huo
Public leaderboards for AI models are read continuously, and attackers can see every published standing. Vote rigging, selective disclosure of private variants, and benchmark conta…
Rank Confidence Sequences:Anytime-valid Leaderboards
Hamed Khosravi, Xiaoming Huo
Leaderboards rank models by their average scores on benchmark items, and they are consulted repeatedly while the evaluation is still running. Existing confidence intervals for a mo…
Beyond "AI Helps Humans": Decision-Targeted Evaluation Design for Human-Agent Teams in the Agentic Era
Hamed Khosravi, Xiaoming Huo
Wherever a coding agent works under engineer supervision, or a clinical model assists a radiologist, the deployment question is whether to keep the human-AI workflow or replace it…
Which LLM for Which Work? Budgeted Model Allocation under Uncertain Evaluation
Hamed Khosravi, Xiaoming Huo
A company with a fixed artificial intelligence (AI) budget must decide which large language model (LLM) handles each recurring workload. What it lacks is the quality table, how wel…
Conformal Selective Acting: Anytime-Valid Risk Control for RLVR-Trained LLMs
Hamed Khosravi, Xiaoming Huo
A local specialist LLM, fine-tuned with reinforcement learning from verifiable rewards (RLVR) on operator-local data, is installed in a regulated organization with per-deployment e…
Catching a Moving Subspace: Low-Rank Bandits Beyond Stationarity
Hamed Khosravi, Xiaoming Huo
Many bandit deployments (recommendation, clinical dosing, ad targeting) share two facts prior work handles only in isolation: rewards live on a low-dimensional latent subspace, and…