Search Results for author:
Found 5 papers, 1 papers with code
PiCO: Peer Review in LLMs based on the Consistency Optimization
Existing large language models (LLMs) evaluation methods typically focus on testing the performance on some closed-environment and domain-specific benchmarks with human annotations.
Towards Better Query Classification with Multi-Expert Knowledge Condensation in JD Ads Search
To overcome this challenge, in this paper, we propose knowledge condensation (KC), a simple yet effective knowledge distillation framework to boost the classification performance of the online FastText model under strict low latency constraints.
Data Provenance via Differential Auditing
In this paper, we introduce Data Provenance via Differential Auditing (DPDA), a practical framework for auditing data provenance with a different approach based on statistically significant differentials, i. e., after carefully designed transformation, perturbed input data from the target model's training set would result in much more drastic changes in the output than those from the model's non-training set.
Improving deep forest by confidence screening
Most studies about deep learning are based on neural network models, where many layers of parameterized nonlinear differentiable modules are trained by back propagation.
Unorganized Malicious Attacks Detection
This work considers a different attack style: unorganized malicious attacks, where attackers individually utilize a small number of user profiles to attack different items without any organizer.
