4 papers
ChartProbe: A Diagnostic Study on Visual Reasoning through Perception, Grounding, and Simple Reasoning
Mahsa Khoshnoodi, Sarah Adel Bargal
Vision-language models (VLMs) remain unreliable on chart questions that require reasoning over visual quantities, and this weakness is usually attributed to a reasoning deficit and…
PROVE: Training-Free Prompt Recovery using Verifiable Evidence
Rupayan Mallick, Mahsa Khoshnoodi, Sarah Adel Bargal
Modern text-to-image models can generate highly realistic images from natural-language prompts, while recent advances in prompt inversion have made it increasingly feasible to reco…
Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive Principles
Devichand Budagam, Ashutosh Kumar, Mahsa Khoshnoodi +3
Assessing the effectiveness of large language models (LLMs) in performing different tasks is crucial for understanding their strengths and weaknesses. This paper presents Hierarchi…
A Comprehensive Survey of Accelerated Generation Techniques in Large Language Models
Mahsa Khoshnoodi, Vinija Jain, Mingye Gao +2
Despite the crucial importance of accelerating text generation in large language models (LLMs) for efficiently producing content, the sequential nature of this process often leads…