Debanshu Das

Machine translation benchmarks have functionally saturated, but pairing human-authored failure cases with deterministic verification rules reveals critical multimodal blind spots that automated metrics consistently miss.

Fluent language from an agentic IR system can be dangerously deceptive, masking critical errors in planning, retrieval, reasoning, and execution that accumulate over time.

LLM-powered multi-agent architectures are poised to revolutionize video recommendation by enabling precise, explainable, and adaptive recommendations that surpass the limitations of static, single-model systems.