Ufaq Khan

Chemical structure of a molecule featuring a central ring with alternating single and double bonds, connected to various side groups including a nitrogen atom bonded to a methyl group, a hydroxyl group, and a carboxyl group. The image highlights the arrangement of atoms and bonds to show the molecule’s shape and functional parts important for its chemical behavior. MedObvious: Exposing the Medical Moravec’s Paradox in VLMs via Clinical Triage

Ufaq Khan, Umair Nawaz, Lekkala Sai Teja, Numan Saeed et autres

ae, in, gb (code pays fourni par la source)

PolyAlign: Conditional Human-Distribution Alignment

L D M S S Teja, Ufaq Khan, Sathira Silva, 吴晓 et autres

Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective for improving average helpfulness, this can suppress the natural variation of human responses across languages, tasks, and dialogue settings. We …

PolyAlign: Conditional Human-Distribution Alignment

L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva, 吴晓 et autres

Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective for improving average helpfulness, this can suppress the natural variation of human responses across languages, tasks, and dialogue settings. We …

in, ae (code pays fourni par la source)

MMClima: A Framework for Multimodal Climate Science Data and Evaluation

Muhammad Umer Sheikh, Hassan Abid, Khawar Shehzad, Ufaq Khan et autres

Climate change research increasingly requires AI systems that reason across text, dynamic visual content, and scientific figures, yet existing climate QA benchmarks are small, mostly textual, and cover a narrow range of models. We introduce MMClima, a large-scale multimodal climate question answering …

MMClima: A Framework for Multimodal Climate Science Data and Evaluation

Muhammad Umer Sheikh, Hassan Abid, Khawar Shehzad, Ufaq Khan et autres

Climate change research increasingly requires AI systems that reason across text, dynamic visual content, and scientific figures, yet existing climate QA benchmarks are small, mostly textual, and cover a narrow range of models. We introduce MMClima, a large-scale multimodal climate question answering …

PathWISE: Multi-Agent Cancer Pathway Triaging Ontology Learning from Clinical Flowcharts

Sofiat Abioye, Ufaq Khan, Shazad Ashraf, Mohammed Adil Butt et autres

Clinical pathways are disseminated as visual flowcharts where spatial topology, arrow direction, colour coding, and font weight encode critical triage logic that remains inaccessible to computational systems. We present PathWISE, a five-phase pipeline combining four LLM-based agents with a deterministic depth-first search …

RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing

Sofiat Abioye, Ufaq Khan, Shazad Ashraf, Anusha Jose et autres

Urgent suspected colorectal cancer (CRC) referrals create operational bottlenecks because semi-structured clinical documents often require manual review and transcription. The original RAPTOR system used Large Language Models for structured extraction but relied on a separate OCR stage, making it vulnerable to handwriting, …

Not All Modalities Are Equal: Instruction-Aware Gating for Multimodal Videos

Bonan Ding, Umair Nawaz, Ufaq Khan, Abdelrahman Shaker et autres

Pre-trained video large language models excel at visual reasoning. However, they struggle when videos arrive with auxiliary streams, such as audio, depth map, or dense temporal evidence. In such a scenario, uniform fusion induces modality interference, allowing irrelevant channels to distract the …

PathWISE: Multi-Agent Cancer Pathway Triaging Ontology Learning from Clinical Flowcharts

Sofiat Abioye, Ufaq Khan, Shazad Ashraf, Mohammed Adil Butt et autres

Clinical pathways are disseminated as visual flowcharts where spatial topology, arrow direction, colour coding, and font weight encode critical triage logic that remains inaccessible to computational systems. We present PathWISE, a five-phase pipeline combining four LLM-based agents with a deterministic depth-first search …

gb, ae, qa (code pays fourni par la source)

RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing

Sofiat Abioye, Ufaq Khan, Shazad Ashraf, Anusha Jose et autres

Urgent suspected colorectal cancer (CRC) referrals create operational bottlenecks because semi-structured clinical documents often require manual review and transcription. The original RAPTOR system used Large Language Models for structured extraction but relied on a separate OCR stage, making it vulnerable to handwriting, …

gb, ae, us (code pays fourni par la source)

Not All Modalities Are Equal: Instruction-Aware Gating for Multimodal Videos

Bonan Ding, Umair Nawaz, Ufaq Khan, Abdelrahman Shaker et autres

Pre-trained video large language models excel at visual reasoning. However, they struggle when videos arrive with auxiliary streams, such as audio, depth map, or dense temporal evidence. In such a scenario, uniform fusion induces modality interference, allowing irrelevant channels to distract the …

cn, ca, se (code pays fourni par la source)

Aurora: Adaptive Unified Representation for Robust Ultrasound Analysis

Ufaq Khan, L D M S Sai Teja, Ayuba Shakiru, Mai A. Shaaban et autres

Ultrasound images can vary widely across scanners, operators, and anatomical targets, so models trained in one setting often generalize poorly to new hospitals and clinical conditions. The Foundation Model Challenge for Ultrasound Image Analysis (FMC-UIA) reflects this scenario by requiring a single …

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