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By embedding online learning directly into LLM call latencies, this framework can cut query costs by nearly 8x, revolutionizing how we optimize semantic data processing.
Standard LLM agents lose critical plan information when evicted from context, leading to a staggering 34.7% drop in task success rates.
Current multimodal agents navigating document collections achieve human-level accuracy through brute-force search, highlighting a critical gap in strategic reasoning and planning.
