15 papers
Memorization Diagnostics for Code LLMs Should be Scale-Aware
Prateek Kumar Rajput, Abdoul Aziz Bonkoungou, Alberick Euraste Djiré +6
The extent to which large language models for code rely on memorization over genuine understanding remains highly debated. While current literature frequently reports widespread me…
Agent Skill Framework: Perspectives on the Potential of Small to Medium Language Models in Industrial Environments
Yangjie Xu, Lujun Li, Lama Sleem +6
Agent skills are widely supported by major agentic frameworks and perform well with proprietary models, yet their effectiveness for small and medium-sized open source language mode…
Empirical Study for Structured Output Control in LLMs for Software Engineering
Yewei Song, Prateek Rajput, Tiezhu Sun +3
LLM-generated outputs in software engineering rarely exist in isolation. They must plug into toolchains, APIs, and data pipelines that impose strict, often organization-specific st…
The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models
Lujun Li, Lama Sleem, Niccolo Gentile +4
Recent vision-language models (VLMs) excel at multimodal understanding and reasoning, yet their fine-grained visual perception remains underexplored. A natural extension of ``How m…
The Necessity of Setting Temperature in LLM-as-a-Judge
Lujun Li, Lama Sleem, Yangjie Xu +4
Using large language models (LLMs) as judges for evaluating model outputs has emerged as an important paradigm for automated evaluation. However, the choice of decoding temperature…
Evaluation Drift in LLM Personality Induction: Are We Moving the Goalpost?
Prateek Rajput, Yewei Song, Iyiola E. Olatunji +2
Can large language models reliably express a human-like personality, or are they merely mimicking surface cues without a stable underlying profile? To investigate this, we induce p…