… An LLM might give a highly fluent, partially correct answer that recommends the wrong material grade or violates a national standard—a critical failure in the real world. …
… The following papers were recommended by the Semantic Scholar API ADAPT: Benchmarking Commonsense Planning under Unspecified Affordance Constraints 2026 From Where Things Are to What They Are For: Benchmarking Spatial-Functional Intelligence in Multimodal LLMs 2026 Affordance Agent Harness: Verific… …
… Yet, in conversational benchmarks, which simulate real-world customer-centric issue resolution scenarios, these agents frequently fail due to the cascading effects of incorrect decision-making. …
… AI-generated summary Long-context large language models LLMs -for example, Gemini-3.1-Pro and Qwen-3.5-are widely used to empower many real-world applications, such as retrieval-augmented generation, autonomous agents, and AI assistants. …
… Instructions to the chatbot were sometimes lengthy and filled with details that could be either extraneous or critical clues to the correct diagnosis. “We went the extra step and showed that this performance also works in the real world,” Rodman says. …
… Overall, we show that provenance tracking for generated code can be made practical for real-world LLM systems. …
… However, existing research mainly focuses on static scam detection or synthetic scams, leaving open whether language models can understand how real-world scams progress over time. …
… Real-world data adds real-world flavor. …
… Not only does VideoPrism consistently outperform strong baselines, but its unique ability to generalize positions it well for tackling an array of real-world applications. …
… They also evaluated the accuracy of the quantized models, using Language Model Evaluation Harness . …