· ai
[Paper] Layer-wise Positional Bias in Short-Context Language Modeling
Language models often show a preference for using information from specific positions in the input regardless of semantic relevance. While positional bias has b...
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- · ai
[Paper] SearchAttack: Red-Teaming LLMs against Real-World Threats via Framing Unsafe Web Information-Seeking Tasks
Recently, people have suffered and become increasingly aware of the unreliability gap in LLMs for open and knowledge-intensive tasks, and thus turn to search-au...
- · ai
[Paper] KDCM: Reducing Hallucination in LLMs through Explicit Reasoning Structures
To mitigate hallucinations in large language models (LLMs), we propose a framework that focuses on errors induced by prompts. Our method extends a chain-style k...
- · ai
[Paper] Analyzing Reasoning Consistency in Large Multimodal Models under Cross-Modal Conflicts
Large Multimodal Models (LMMs) have demonstrated impressive capabilities in video reasoning via Chain-of-Thought (CoT). However, the robustness of their reasoni...
- · devops
[Paper] Hummingbird: SLO-Oriented GPU Preemption at Microsecond-scale
Existing GPU-sharing techniques, including spatial and temporal sharing, aim to improve utilization but face challenges in simultaneously ensuring SLO adherence...
- · ai
[Paper] Bridging the Discrete-Continuous Gap: Unified Multimodal Generation via Coupled Manifold Discrete Absorbing Diffusion
The bifurcation of generative modeling into autoregressive approaches for discrete data (text) and diffusion approaches for continuous data (images) hinders the...
- · software
[Paper] A Systematic Mapping Study on the Debugging of Autonomous Driving Systems
As Autonomous Driving Systems (ADS) progress towards commercial deployment, there is an increasing focus on ensuring their safety and reliability. While conside...
- · software
[Paper] An Ontology-Based Approach to Security Risk Identification of Container Deployments in OT Contexts
In operational technology (OT) contexts, containerised applications often require elevated privileges to access low-level network interfaces or perform administ...
- · ai
[Paper] A Scheduling Framework for Efficient MoE Inference on Edge GPU-NDP Systems
Mixture-of-Experts (MoE) models facilitate edge deployment by decoupling model capacity from active computation, yet their large memory footprint drives the nee...
- · ai
[Paper] Using Small Language Models to Reverse-Engineer Machine Learning Pipelines Structures
Background: Extracting the stages that structure Machine Learning (ML) pipelines from source code is key for gaining a deeper understanding of data science prac...
- · ai
[Paper] Monaas: Mobile Node as a Service for TSCH-based Industrial IoT Networks
The Time-Slotted Channel Hopping (TSCH) mode of IEEE802.15.4 standard provides ultra high end-to-end reliability and low-power consumption for application in fi...
- · software
[Paper] Understanding Specification-Driven Code Generation with LLMs: An Empirical Study Design
Large Language Models (LLMs) are increasingly integrated into software development workflows, yet their behavior in structured, specification-driven processes r...