Saved in:
| Main Authors: | Islam, Mohammed Saidul, Baghbanzadeh, Negin, Kohankhaki, Farnaz, Cheraghi, Afshin, Kore, Ali, Mehdi, Shayaan, Dolatabadi, Elham, Afkanpour, Arash |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.18824 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Automated Capability Evaluation of Foundation Models
by: Afkanpour, Arash, et al.
Published: (2025)
by: Afkanpour, Arash, et al.
Published: (2025)
Open-PMC-18M: A High-Fidelity Large Scale Medical Dataset for Multimodal Representation Learning
by: Baghbanzadeh, Negin, et al.
Published: (2025)
by: Baghbanzadeh, Negin, et al.
Published: (2025)
Consistency-Guided Asynchronous Contrastive Tuning for Few-Shot Class-Incremental Tuning of Foundation Models
by: Roy, Shuvendu, et al.
Published: (2024)
by: Roy, Shuvendu, et al.
Published: (2024)
Similarity-Aware Token Pruning: Your VLM but Faster
by: Jeddi, Ahmadreza, et al.
Published: (2025)
by: Jeddi, Ahmadreza, et al.
Published: (2025)
Practical Guide for Causal Pathways and Sub-group Disparity Analysis
by: Kohankhaki, Farnaz, et al.
Published: (2024)
by: Kohankhaki, Farnaz, et al.
Published: (2024)
A Shared Encoder Approach to Multimodal Representation Learning
by: Roy, Shuvendu, et al.
Published: (2025)
by: Roy, Shuvendu, et al.
Published: (2025)
Advancing Medical Representation Learning Through High-Quality Data
by: Baghbanzadeh, Negin, et al.
Published: (2025)
by: Baghbanzadeh, Negin, et al.
Published: (2025)
Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions
by: Hoque, Enamul, et al.
Published: (2024)
by: Hoque, Enamul, et al.
Published: (2024)
Benchmarking Vision-Language Contrastive Methods for Medical Representation Learning
by: Roy, Shuvendu, et al.
Published: (2024)
by: Roy, Shuvendu, et al.
Published: (2024)
When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains
by: Jeddi, Ahmadreza, et al.
Published: (2026)
by: Jeddi, Ahmadreza, et al.
Published: (2026)
Exploring Bias and Prediction Metrics to Characterise the Fairness of Machine Learning for Equity-Centered Public Health Decision-Making: A Narrative Review
by: Raza, Shaina, et al.
Published: (2024)
by: Raza, Shaina, et al.
Published: (2024)
BanglaSummEval: Reference-Free Factual Consistency Evaluation for Bangla Summarization
by: Rafid, Ahmed, et al.
Published: (2026)
by: Rafid, Ahmed, et al.
Published: (2026)
BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP
by: Kabir, Mohsinul, et al.
Published: (2023)
by: Kabir, Mohsinul, et al.
Published: (2023)
Template-Based Probes Are Imperfect Lenses for Counterfactual Bias Evaluation in LLMs
by: Kohankhaki, Farnaz, et al.
Published: (2024)
by: Kohankhaki, Farnaz, et al.
Published: (2024)
Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs
by: Islam, Mohammed Saidul, et al.
Published: (2024)
by: Islam, Mohammed Saidul, et al.
Published: (2024)
Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization
by: Rahman, Mizanur, et al.
Published: (2026)
by: Rahman, Mizanur, et al.
Published: (2026)
FAIR Enough: How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training?
by: Raza, Shaina, et al.
Published: (2024)
by: Raza, Shaina, et al.
Published: (2024)
Judging the Judges: Can Large Vision-Language Models Fairly Evaluate Chart Comprehension and Reasoning?
by: Laskar, Md Tahmid Rahman, et al.
Published: (2025)
by: Laskar, Md Tahmid Rahman, et al.
Published: (2025)
Improving Automatic Evaluation of Large Language Models (LLMs) in Biomedical Relation Extraction via LLMs-as-the-Judge
by: Laskar, Md Tahmid Rahman, et al.
Published: (2025)
by: Laskar, Md Tahmid Rahman, et al.
Published: (2025)
Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers
by: Wang, Yuxia, et al.
Published: (2023)
by: Wang, Yuxia, et al.
Published: (2023)
DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts
by: Islam, Mohammed Saidul, et al.
Published: (2024)
by: Islam, Mohammed Saidul, et al.
Published: (2024)
When Can We Trust LLMs in Mental Health? Large-Scale Benchmarks for Reliable LLM Evaluation
by: Badawi, Abeer, et al.
Published: (2025)
by: Badawi, Abeer, et al.
Published: (2025)
Lost in Translation: Do LVLM Judges Generalize Across Languages?
by: Laskar, Md Tahmid Rahman, et al.
Published: (2026)
by: Laskar, Md Tahmid Rahman, et al.
Published: (2026)
DashboardQA: Benchmarking Multimodal Agents for Question Answering on Interactive Dashboards
by: Kartha, Aaryaman, et al.
Published: (2025)
by: Kartha, Aaryaman, et al.
Published: (2025)
The Perils of Chart Deception: How Misleading Visualizations Affect Vision-Language Models
by: Mahbub, Ridwan, et al.
Published: (2025)
by: Mahbub, Ridwan, et al.
Published: (2025)
LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs
by: Davoodi, Arash Gholami, et al.
Published: (2024)
by: Davoodi, Arash Gholami, et al.
Published: (2024)
From Charts to Fair Narratives: Uncovering and Mitigating Geo-Economic Biases in Chart-to-Text
by: Mahbub, Ridwan, et al.
Published: (2025)
by: Mahbub, Ridwan, et al.
Published: (2025)
FineMath: A Fine-Grained Mathematical Evaluation Benchmark for Chinese Large Language Models
by: Liu, Yan, et al.
Published: (2024)
by: Liu, Yan, et al.
Published: (2024)
Academic case reports lack diversity: Assessing the presence and diversity of sociodemographic and behavioral factors related to Post COVID-19 Condition
by: Florez, Juan Andres Medina, et al.
Published: (2025)
by: Florez, Juan Andres Medina, et al.
Published: (2025)
A Flexible Fairness Framework with Surrogate Loss Reweighting for Addressing Sociodemographic Disparities
by: Xu, Wen, et al.
Published: (2025)
by: Xu, Wen, et al.
Published: (2025)
Deploying Tiny LVLM Judges for Real-World Evaluation of Chart Models: Lessons Learned and Best Practices
by: Laskar, Md Tahmid Rahman, et al.
Published: (2025)
by: Laskar, Md Tahmid Rahman, et al.
Published: (2025)
Evaluating Progress in Graph Foundation Models: A Comprehensive Benchmark and New Insights
by: Yu, Xingtong, et al.
Published: (2026)
by: Yu, Xingtong, et al.
Published: (2026)
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents
by: Arjmand, Mehdi, et al.
Published: (2024)
by: Arjmand, Mehdi, et al.
Published: (2024)
SparseTransX: Efficient Training of Translation-Based Knowledge Graph Embeddings Using Sparse Matrix Operations
by: Anik, Md Saidul Hoque, et al.
Published: (2025)
by: Anik, Md Saidul Hoque, et al.
Published: (2025)
FREB-TQA: A Fine-Grained Robustness Evaluation Benchmark for Table Question Answering
by: Zhou, Wei, et al.
Published: (2024)
by: Zhou, Wei, et al.
Published: (2024)
VLDBench Evaluating Multimodal Disinformation with Regulatory Alignment
by: Raza, Shaina, et al.
Published: (2025)
by: Raza, Shaina, et al.
Published: (2025)
C-FAITH: A Chinese Fine-Grained Benchmark for Automated Hallucination Evaluation
by: Zhang, Xu, et al.
Published: (2025)
by: Zhang, Xu, et al.
Published: (2025)
LLM-Based Data Science Agents: A Survey of Capabilities, Challenges, and Future Directions
by: Rahman, Mizanur, et al.
Published: (2025)
by: Rahman, Mizanur, et al.
Published: (2025)
ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering
by: Masry, Ahmed, et al.
Published: (2025)
by: Masry, Ahmed, et al.
Published: (2025)
P2P: Automated Paper-to-Poster Generation and Fine-Grained Benchmark
by: Sun, Tao, et al.
Published: (2025)
by: Sun, Tao, et al.
Published: (2025)
Similar Items
-
Automated Capability Evaluation of Foundation Models
by: Afkanpour, Arash, et al.
Published: (2025) -
Open-PMC-18M: A High-Fidelity Large Scale Medical Dataset for Multimodal Representation Learning
by: Baghbanzadeh, Negin, et al.
Published: (2025) -
Consistency-Guided Asynchronous Contrastive Tuning for Few-Shot Class-Incremental Tuning of Foundation Models
by: Roy, Shuvendu, et al.
Published: (2024) -
Similarity-Aware Token Pruning: Your VLM but Faster
by: Jeddi, Ahmadreza, et al.
Published: (2025) -
Practical Guide for Causal Pathways and Sub-group Disparity Analysis
by: Kohankhaki, Farnaz, et al.
Published: (2024)