Papers3

#multi-turn dialogue

CAR-bench: Evaluating the Consistency and Limit-Awareness of LLM Agents under Real-World Uncertainty

Johannes Kirmayr, Lukas Stappen et al.Jan 29arXiv

CAR-bench is a new 'driving test' for AI assistants that checks if they can stay careful, honest, and consistent during real back-and-forth conversations in a car.

#LLM agents#benchmarking#consistency

Not triaged yet

GameTalk: Training LLMs for Strategic Conversation

Intermediate

Victor Conchello Vendrell, Max Ruiz Luyten et al.Jan 22arXiv

Large language models usually get judged one message at a time, but many real tasks need smart planning across a whole conversation.

#strategic conversation#reinforcement learning for LLMs#multi-turn dialogue

Not triaged yet

A Benchmark and Agentic Framework for Omni-Modal Reasoning and Tool Use in Long Videos

Intermediate

Mohammed Irfan Kurpath, Jaseel Muhammad Kaithakkodan et al.Dec 18arXiv

This paper builds a new test, LongShOTBench, to check if AI can truly understand long videos by using sight, speech, and sounds together.

#long-form video understanding#multimodal reasoning#audio-visual-speech alignment

Not triaged yet