6 citations · 7 across the 4 of their papers we have counts for
4 papers
Reasoning emerges from constrained inference manifolds in large language models
Yanbiao Ma, Fei Luo, Linfeng Zhang +10
Reasoning in large language models is predominantly evaluated through labeled benchmarks, conflating task performance with the quality of internal inference. Here we study reasonin…
ICLEval: Evaluating In-Context Learning Ability of Large Language Models
Wentong Chen, Yankai Lin, ZhenHao Zhou +4
In-Context Learning (ICL) is a critical capability of Large Language Models (LLMs) as it empowers them to comprehend and reason across interconnected inputs. Evaluating the ICL abi…
An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models
Qi Liu, Gang Guo, Jiaxin Mao +5
With the development of pre-trained language models, the dense retrieval models have become promising alternatives to the traditional retrieval models that rely on exact match and…
UFIN: Universal Feature Interaction Network for Multi-Domain Click-Through Rate Prediction
Zhen Tian, Changwang Zhang, Wayne Xin Zhao +3
Click-Through Rate (CTR) prediction, which aims to estimate the probability of a user clicking on an item, is a key task in online advertising. Numerous existing CTR models concent…