IVQ 301-350

Section 31: Multilingual and Cross-Cultural GenAI (10 Questions)

  1. How do GenAI models handle multilingual inputs?

  2. What are alignment challenges when generating content in multiple languages?

  3. How do you evaluate translation accuracy in low-resource languages?

  4. How would you fine-tune a model to perform better on a specific regional dialect?

  5. What are the best multilingual open-source LLMs available today?

  6. How do you ensure cultural sensitivity in multilingual GenAI output?

  7. How do embeddings behave across languages? Are they comparable?

  8. What are strategies to prevent code-mixing errors in multilingual chatbots?

  9. How do GenAI models handle right-to-left (RTL) scripts like Arabic or Hebrew?

  10. What are multilingual benchmarks like XNLI or XTREME, and why do they matter?

Section 32: Tool Integration and Automation (10 Questions)

  1. How would you architect a GenAI system that automatically fills forms using PDFs?

  2. How can GenAI be used to control CLI or OS-level tools safely?

  3. What’s the difference between Zapier MCP and OpenAI function calling?

  4. How do you trigger real-world automation (like sending emails or notifications) using GenAI?

  5. How do you use Selenium or Playwright with GenAI for browser control?

  6. How can you use GenAI for test automation in software QA?

  7. How do you integrate GenAI with calendar tools for smart scheduling?

  8. How do you ensure safe tool use in LLM-powered autonomous agents?

  9. What are common tool abstractions in LangChain or AutoGen?

  10. How do you manage API credentials securely in GenAI workflows?

Section 33: Testing & Evaluation Strategies (10 Questions)

  1. How do you write unit tests for GenAI prompt outputs?

  2. What is prompt fuzzing and why is it important?

  3. How do you conduct regression testing for GenAI behavior?

  4. How can you simulate adversarial attacks during model testing?

  5. What are gold-standard responses in GenAI evaluation?

  6. How do you evaluate hallucination vs. paraphrasing vs. error?

  7. What’s the best way to do continuous integration for GenAI prompts?

  8. What metrics would you track in a GenAI system post-release?

  9. How do you identify slow degradation of GenAI model quality?

  10. How do you validate performance on rare edge cases?

Section 34: Agentic Reasoning & Task Planning (10 Questions)

  1. How do LLM agents decide when to use tools vs. generate answers?

  2. How do you enable recursive self-reflection in agents?

  3. What’s the difference between plan-and-execute vs. chain-of-thought approaches?

  4. How would you implement a research agent that performs web searches and writes a report?

  5. How do you tune an agent’s decision-making loop for complex task completion?

  6. What is dynamic memory injection in agent design?

  7. How do you use graph structures for tracking agent plans?

  8. What is inter-agent communication and when is it useful?

  9. How would you simulate user feedback in agent training?

  10. How can agents collaborate to summarize, critique, and improve a document?

Section 35: Temporal & Sequential Reasoning (10 Questions)

  1. How do GenAI models handle time-based logic or sequences of events?

  2. How would you get an LLM to generate accurate timelines?

  3. What’s the difference between temporal inference and causal reasoning?

  4. How do you evaluate event consistency in long-context generation?

  5. How do LLMs fail at reasoning about calendars or durations, and how do you fix it?

  6. How would you simulate memory evolution over time for an agent?

  7. How can GenAI track state changes in a long conversation?

  8. How do you implement reminder and follow-up functionality in a GenAI assistant?

  9. What are ways to encode temporal facts into retrieval systems?

  10. How would you compare two GenAI outputs for narrative coherence over time?

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