Xi Wang

A Tool for Supporting Requirements Formalization Based on Specification Pattern Knowledge

2015

Despite the effectiveness of requirements formalization in producing accurate requirements documentation, thistechnique can hardly be accepted by software industry mainlydue to the difficulty in manipulating formal notations by practitioners. To handle the challenge, this paper …

Reliability-Constrained Resource Allocation with Weighted SRLG for Distributed Clouds

2015 · Optical Fiber Communication Conference

We propose heuristics to allocate virtual machines among distributed data centers for a cloud request. Our objective is to minimize the maximum delay between selected data centers, while considering the reliability and computing resource constraints.

Nickel: a framework for design and verification of information flow control systems

2018 · Operating Systems Design and Implementation

Nickel is a framework that helps developers design and verify information flow control systems by systematically eliminating covert channels inherent in the interface, which can be exploited to circumvent the enforcement of information flow policies. …

Snap

2019

This paper presents our design and experience with a microkernel-inspired approach to host networking called Snap. Snap is a userspace networking system that supports Google's rapidly evolving needs with flexible modules that implement a range …

MetaASSIST: Robust Dialogue State Tracking with Meta Learning

2022

Existing dialogue datasets contain lots of noise in their state annotations. Such noise can hurt model training and ultimately lead to poor generalization performance. A general framework named ASSIST has recently been proposed to train …

Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentation

2023 · arXiv (Cornell University)

Conversational Recommendation System (CRS) is a rapidly growing research area that has gained significant attention alongside advancements in language modelling techniques. However, the current state of conversational recommendation faces numerous challenges due to its relative …

An Empirical Investigation of Domain Adaptation Ability for Chinese Spelling Check Models

2024 · arXiv (Cornell University)

Chinese Spelling Check (CSC) is a meaningful task in the area of Natural Language Processing (NLP) which aims at detecting spelling errors in Chinese texts and then correcting these errors. However, CSC models are based …

Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning

2025

Recent advancements in large language models (LLMs) have sparked significant interest in the automatic generation of Register Transfer Level (RTL) designs, particularly using Verilog. Current research on this topic primarily focuses on pre-training and instruction …

Progressive Depth Up-scaling via Optimal Transport

2025 · arXiv (Cornell University)

Scaling Large Language Models (LLMs) yields performance gains but incurs substantial training costs. Depth up-scaling offers training efficiency by adding new layers to pre-trained models. However, most existing methods copy or average weights from base …

DeepRec: Towards a Deep Dive Into the Item Space with Large Language Model Based Recommendation

2025 · arXiv (Cornell University)

Recently, large language models (LLMs) have been introduced into recommender systems (RSs), either to enhance traditional recommendation models (TRMs) or serve as recommendation backbones. However, existing LLM-based RSs often do not fully exploit the complementary …

Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation

2025 · arXiv (Cornell University)

This paper focus on few-shot object detection~(FSOD) and instance segmentation~(FSIS), which requires a model to quickly adapt to novel classes with a few labeled instances. The existing methods severely suffer from bias classification because of …

Decomposing Prompts, Composing Actions: A Multi-Granularity Prompting Approach for Incremental Action Learning

2026 · Proceedings of the AAAI Conference on Artificial Intelligence

Continual learning for action recognition is a critical capability for next-generation Extended Reality (XR) systems. Yet it faces a severe real-world challenge: strict user privacy that prohibits data rehearsal. While recent prompt-based continual learning methods …