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ACM India Winter School 2026

Multimodal and Reasoning-Aware Generative AI

From Foundations and Large Language Models to Multimodal Reasoning and Trustworthy AI

Jointly hosted by Information Retrieval & Intelligent Semantics Lab and Center of Intelligence Robotics, IIIT Allahabad in conjunction with ACM India Council

21st Dec 2026 – 01st Jan 2027 IIIT Allahabad, Uttar Pradesh, India 10 Days Intensive In-Person School
10 Days
6 Modules
5+ Expert Speakers
16 Hands-on Sessions
Scientific Rationale

Bridging Generation and Reasoning in Generative AI

Generative Artificial Intelligence (GenAI), powered by large language models, foundation models, and multimodal architectures, is transforming applications such as conversational AI, text summarization, question answering, document understanding, and scientific discovery. However, current generative models can still struggle with systematic reasoning, factual grounding, hallucination, explainability, robustness, and safety.

The ACM India Winter School on “Multimodal and Reasoning-Aware Generative AI” aims to address these challenges through a progressive combination of foundational concepts, expert lectures, and hands-on learning. The programme covers modern paradigms including transformers and LLMs, instruction learning, Chain-of-Thought and structured prompting, Retrieval-Augmented Generation (RAG), neuro-symbolic reasoning, hallucination and faithfulness evaluation, vision-language models, multimodal grounding, and multisource data fusion.

The school further emphasizes responsible and trustworthy GenAI, covering bias, fairness, safety, alignment, and deployment considerations. Hands-on experiments and group mini-projects will enable participants to translate theoretical concepts into practical AI systems and develop a foundation for further research and innovation in Generative AI.

HOST INSTITUTION

Indian Institute of Information Technology Allahabad (IIITA)

PROGRAM DURATION

10 Instructional Days (21st Dec 2026 – 01st Jan 2027)

PROGRAM FORMAT

Morning Lectures, Afternoon Hands-on Labs & Mini-Projects

CERTIFICATION

Joint Certificate by ACM India & IIIT Allahabad

Core Focus

Objectives of the School

GenAI Foundations

Introduce transformers, pretraining objectives, instruction tuning, parameter-efficient fine-tuning (PEFT), and alignment.

Reasoning-Aware Models

Master Chain-of-Thought (CoT), structured prompting, RAG, and neuro-symbolic/program-aided approaches.

Multimodal Generative AI

Gain hands-on training building vision-language models, cross-modal pipelines, and multimodal RAG.

Robustness & Evaluation

Detect hallucinations, benchmark reasoning faithfulness, evaluate bias, safety, and responsible AI alignment.

Hands-on Experience

16 interactive lab sessions with real-world LLM frameworks, vector databases, and multimodal models.

Mentored Mini-Projects

Formulate research problems, implement novel solutions in groups, and present findings before an expert panel.

Target Audience

Prerequisites: Basic machine learning concepts and Python programming proficiency.

Final-Year Undergraduate Students Master’s Students (M.Tech/MS) Ph.D. Scholars Early-Career Researchers
Curriculum

6 Comprehensive Modules

Module 1

Foundations of Generative AI

  • Language modeling & transformer architectures
  • Tokenization algorithms & pretraining objectives
  • Fine-tuning, PEFT, and instruction learning
Module 2

Reasoning with Language Models

  • Chain-of-thought & structured prompting
  • Retrieval-augmented generation (RAG)
  • Program-aided & neuro-symbolic reasoning
Module 3

Evaluation, Robustness & Explainability

  • Hallucination detection and mitigation
  • Faithfulness and reasoning benchmarks
  • Explainable NLP & model interpretability
Module 4

Multimodal & Grounded Generative AI

  • Vision-Language Models (VLMs)
  • Knowledge grounding in visual domains
  • Multisource data fusion & multimodal RAG
Module 5

Responsible & Trustworthy GenAI

  • Bias, fairness, and toxicity assessment
  • Safety guardrails, alignment (RLHF/DPO)
  • Secure deployment considerations
Module 6

Hands-on Labs & Mini Projects

  • 16 guided coding experiments in Python/PyTorch
  • Multimodal reasoning pipeline implementation
  • Group projects under mentor guidance
Program Schedule

11-Day Detailed Timetable

Leadership

Academic & Local Coordinators

Academic Coordinator

Dr. Nipun Batra

Dr. Nipun Batra

Academic Coordinator
Associate Professor, Department of Computer Science & Engineering
IIT Gandhinagar, Gujarat, India

Local Coordinators

Dr. Naveen Saini

Dr. Naveen Saini

Local Coordinator
Assistant Professor, Department of Information Technology
IIIT Allahabad, Uttar Pradesh, India
Prof. Sonali Agarwal

Prof. Sonali Agarwal

Local Coordinator
Professor, Department of Information Technology
IIIT Allahabad, Uttar Pradesh, India
Host Campus

Indian Institute of Information Technology Allahabad

IIIT Allahabad is an Institute of National Importance established by the Government of India. It represents a premier center of excellence in Information Technology and allied domains, equipped with state-of-the-art AI computing labs and residential infrastructure.

Participants will have access to high-performance computing clusters and high-speed network access for hands-on sessions throughout the 10 days.

  • Devghat, Jhalwa, Prayagraj (Allahabad), Uttar Pradesh - 211015
  • On-campus student hostel accommodation provided for participants.
IIIT Allahabad Campus