We have 4 of 11 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Although reinforcement learning (RL) post-training repairs the localized segmental errors of zero-shot text-to-speech (TTS), arriving at a working recipe still relies on tedious manual tuning, and whether LLM agents can take over this research pipeline is unclear. We investigate this question with AgenticTTS-Forge, a c...
GDP-RAG is proposed, a plan-based framework that targets only the information delta based on three simple design choices, and achieves the highest accuracy among all compared systems while maintaining a cost-of-pass of 0.51.
This work proposes to optimize the benchmark generation workflow itself end to end with MetaBench-Harness, a dual-loop search framework that enables multi-dimensional evolution, steadily improving evolution reasonableness, benchmark competency, and evaluator robustness across successive rounds.
This paper introduces DominoTree, a training-free best-first draft tree scored by Domino's conditional (non-factorized) correction along each root-to-node path, made practical by restricting the per-node correction to a candidate top-M.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
