3 citations · 5 across the 6 of their papers we have counts for
7 papers
From Prompt Rules to Golden Data Model: Production-Scale Generation of Personalized, Compliant Pharmaceutical Claims
Suyash Mishra, Qiang Li, Subhabrata Adak +3
Large language models (LLMs) are increasingly used to generate domain-specific commercial & medical content (e.g., claims, statements, and promotional phrases) in regulated industr…
Are Two LLMs Better Than One? A Student-Teacher Dual-Head LLMs Architecture for Pharmaceutical Content Optimization
Suyash Mishra, Qiang Li, Anubhav Girdhar
Large Language Models (LLMs) are increasingly used for content creation in regulated domains such as pharmaceuticals, where content must be medical accurate and legally compliant.…
From Understanding to Engagement: Personalized pharmacy Video Clips via Vision Language Models (VLMs)
Suyash Mishra, Qiang Li, Srikanth Patil +1
Vision Language Models (VLMs) are poised to revolutionize the digital transformation of pharmacyceutical industry by enabling intelligent, scalable, and automated multi-modality co…
Scaling Vision Language Models for Pharmaceutical Long Form Video Reasoning on Industrial GenAI Platform
Suyash Mishra, Qiang Li, Srikanth Patil +2
Vision Language Models (VLMs) have shown strong performance on multimodal reasoning tasks, yet most evaluations focus on short videos and assume unconstrained computational resourc…
Personalized News Recommendation with Multi-granularity Candidate-aware User Modeling
Qiang Li, Xinze Lin, Shenghao Lv +2
Matching candidate news with user interests is crucial for personalized news recommendations. Most existing methods can represent a user's reading interests through a single profil…
RankPrompt: Step-by-Step Comparisons Make Language Models Better Reasoners
Chi Hu, Yuan Ge, Xiangnan Ma +5
Large Language Models (LLMs) have achieved impressive performance across various reasoning tasks. However, even state-of-the-art LLMs such as ChatGPT are prone to logical errors du…
Unified Hallucination Detection for Multimodal Large Language Models
Xiang Chen, Chenxi Wang, Yida Xue +7
Despite significant strides in multimodal tasks, Multimodal Large Language Models (MLLMs) are plagued by the critical issue of hallucination. The reliable detection of such halluci…