39 citations · 69 across the 9 of their papers we have counts for
9 papers
Signed Rescue Routing: Harm-Aware Cascades for Efficient LLM Inference
Zheyuan Wang, Siyu Li, Peiqiao Song +3
Large language model (LLM) cascades answer easy requests with a small model and escalate selected requests to a larger model. Most routers prioritize examples on which the small mo…
Rethinking One-Shot Federated Graph Learning: Training-Free Statistical Estimation
Shutong Zheng, Sijia Chen
One-shot federated graph learning generally aims to train Graph Neural Networks (GNNs) across clients with disconnected subgraphs in a single communication round. Existing methods…
Semantic Retrieval at Walmart
Alessandro Magnani, Feng Liu, Suthee Chaidaroon +8
In product search, the retrieval of candidate products before re-ranking is more critical and challenging than other search like web search, especially for tail queries, which have…
TableRAG: Million-Token Table Understanding with Language Models
Si-An Chen, Lesly Miculicich, Julian Martin Eisenschlos +7
Recent advancements in language models (LMs) have notably enhanced their ability to reason with tabular data, primarily through program-aided mechanisms that manipulate and analyze…
Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance
Paul Kuo-Ming Huang, Si-An Chen, Hsuan-Tien Lin
Score-based generative models (SGMs) are a popular family of deep generative models that achieve leading image generation quality. Early studies extend SGMs to tackle class-conditi…
Linear Classifier: An Often-Forgotten Baseline for Text Classification
Yu-Chen Lin, Si-An Chen, Jie-Jyun Liu +1
Large-scale pre-trained language models such as BERT are popular solutions for text classification. Due to the superior performance of these advanced methods, nowadays, people ofte…