7 papers
The Radio-Frequency Transformer for Signal Separation
Egor Lifar, Semyon Savkin, Rachana Madhukara +3
We study a problem of signal separation: estimating a signal of interest (SOI) contaminated by an unknown non-Gaussian background/interference. Given the training data consisting o…
GSRM: Generative Speech Reward Model for Speech RLHF
Maohao Shen, Tejas Jayashankar, Osama Hanna +10
Recent advances in speech language models, such as GPT-4o Voice Mode and Gemini Live, have demonstrated promising speech generation capabilities. Nevertheless, the aesthetic natura…
PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
Bowen Jiang, Yuan Yuan, Maohao Shen +13
Personalization is one of the next milestones in advancing AI capability and alignment. We introduce PersonaMem-v2, the state-of-the-art dataset for LLM personalization that simula…
RF Challenge: The Data-Driven Radio Frequency Signal Separation Challenge
Alejandro Lancho, Amir Weiss, Gary C. F. Lee +4
We address the critical problem of interference rejection in radio-frequency (RF) signals using a data-driven approach that leverages deep-learning methods. A primary contribution…
Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search
Maohao Shen, Guangtao Zeng, Zhenting Qi +7
Large language models (LLMs) have demonstrated remarkable reasoning capabilities across diverse domains. Recent studies have shown that increasing test-time computation enhances LL…
Satori-SWE: Evolutionary Test-Time Scaling for Sample-Efficient Software Engineering
Guangtao Zeng, Maohao Shen, Delin Chen +8
Language models (LMs) perform well on standardized coding benchmarks but struggle with real-world software engineering tasks such as resolving GitHub issues in SWE-Bench, especiall…