1 citations · 1 across the 3 of their papers we have counts for
6 papers
3DFroMLLM: 3D Prototype Generation only from Pretrained Multimodal LLMs
Noor Ahmed, Cameron Braunstein, Steffen Eger +1
Recent Multi-Modal Large Language Models (MLLMs) have demonstrated strong capabilities in learning joint representations from text and images. However, their spatial reasoning rema…
ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation
Xiao Wang, Daniil Larionov, Siwei Wu +4
Evaluating the quality of generated text automatically remains a significant challenge. Conventional reference-based metrics have been shown to exhibit relatively weak correlation…
BatchGEMBA: Token-Efficient Machine Translation Evaluation with Batched Prompting and Prompt Compression
Daniil Larionov, Steffen Eger
Recent advancements in Large Language Model (LLM)-based Natural Language Generation evaluation have largely focused on single-example prompting, resulting in significant token over…
TikZero: Zero-Shot Text-Guided Graphics Program Synthesis
Jonas Belouadi, Eddy Ilg, Margret Keuper +5
Automatically synthesizing figures from text captions is a compelling capability. However, achieving high geometric precision and editability requires representing figures as graph…
PromptOptMe: Error-Aware Prompt Compression for LLM-based MT Evaluation Metrics
Daniil Larionov, Steffen Eger
Evaluating the quality of machine-generated natural language content is a challenging task in Natural Language Processing (NLP). Recently, large language models (LLMs) like GPT-4 h…
ScImage: How Good Are Multimodal Large Language Models at Scientific Text-to-Image Generation?
Leixin Zhang, Steffen Eger, Yinjie Cheng +6
Multimodal large language models (LLMs) have demonstrated impressive capabilities in generating high-quality images from textual instructions. However, their performance in generat…