6 papers
Orchestration for Domain-specific Edge-Cloud Language Models
Prasoon Patidar, Alex Crown, Kevin Hsieh +4
The remarkable performance of Large Language Models (LLMs) has inspired many applications, which often necessitate edge-cloud collaboration due to connectivity, privacy, and cost c…
Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks
Yifei Xu, Tusher Chakraborty, Srinagesh Sharma +6
Reinforcement learning (RL) training of large language models (LLMs) on unverifiable tasks is challenging even when a reasonable-quality reference answer is available. We propose a…
AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending
Minyuan Zhou, Yuning Chen, Jiaqi Zheng +11
Operating large-scale anycast networks is challenging because client-to-site mappings often misalign with operator's expectation due to opaque inter-domain routing. We present AnyP…
SibylSense: Adaptive Rubric Learning via Memory Tuning and Adversarial Probing
Yifei Xu, Guilherme Potje, Shivam Shandilya +9
Designing aligned and robust rewards for open-ended generation remains a key barrier to RL post-training. Rubrics provide structured, interpretable supervision, but scaling rubric…
DeepSpecs: Expert-Level Questions Answering in 5G
Aman Ganapathy Manvattira, Yifei Xu, Ziyue Dang +1
5G technology enables mobile Internet access for billions of users. Answering expert-level questions about 5G specifications requires navigating thousands of pages of cross-referen…
RLTHF: Targeted Human Feedback for LLM Alignment
Yifei Xu, Tusher Chakraborty, Emre Kıcıman +11
Fine-tuning large language models (LLMs) to align with user preferences is challenging due to the high cost of quality human annotations in Reinforcement Learning from Human Feedba…