· ai
[Paper] Distribution Matching Variational AutoEncoder
Most visual generative models compress images into a latent space before applying diffusion or autoregressive modelling. Yet, existing approaches such as VAEs a...
-
- · ai
[Paper] Mary, the Cheeseburger-Eating Vegetarian: Do LLMs Recognize Incoherence in Narratives?
Leveraging a dataset of paired narratives, we investigate the extent to which large language models (LLMs) can reliably separate incoherent and coherent stories...
- · devops
[Paper] A Performance Analyzer for a Public Cloud's ML-Augmented VM Allocator
Many operational cloud systems use one or more machine learning models that help them achieve better efficiency and performance. But operators do not have tools...
- · ai
[Paper] Automated Generation of Custom MedDRA Queries Using SafeTerm Medical Map
In pre-market drug safety review, grouping related adverse event terms into standardised MedDRA queries or the FDA Office of New Drugs Custom Medical Queries (O...
- · ai
[Paper] HalluShift++: Bridging Language and Vision through Internal Representation Shifts for Hierarchical Hallucinations in MLLMs
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vision-language understanding tasks. While these models often produce ling...
- · ai
[Paper] When Large Language Models Do Not Work: Online Incivility Prediction through Graph Neural Networks
Online incivility has emerged as a widespread and persistent problem in digital communities, imposing substantial social and psychological burdens on users. Alt...
- · ai
[Paper] Bridging Code Graphs and Large Language Models for Better Code Understanding
Large Language Models (LLMs) have demonstrated remarkable performance in code intelligence tasks such as code generation, summarization, and translation. Howeve...
- · software
[Paper] Reliable agent engineering should integrate machine-compatible organizational principles
As AI agents built on large language models (LLMs) become increasingly embedded in society, issues of coordination, control, delegation, and accountability are ...
- · ai
[Paper] Algorithm-hardware co-design of neuromorphic networks with dual memory pathways
Spiking neural networks excel at event-driven sensing yet maintaining task-relevant context over long timescales. However building these networks in hardware re...
- · devops
[Paper] Bandwidth-Aware Network Topology Optimization for Decentralized Learning
Network topology is critical for efficient parameter synchronization in distributed learning over networks. However, most existing studies do not account for ba...
- · software
[Paper] VP-AutoTest: A Virtual-Physical Fusion Autonomous Driving Testing Platform
The rapid development of autonomous vehicles has led to a surge in testing demand. Traditional testing methods, such as virtual simulation, closed-course, and p...
- · ai
[Paper] AutoICE: Automatically Synthesizing Verifiable C Code via LLM-driven Evolution
Automatically synthesizing verifiable code from natural language requirements ensures software correctness and reliability while significantly lowering the barr...