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Harbin Institute of Technology, Chongqing Research Institute of HIT
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GaLa's hypergraph representation reveals hidden semantic relationships in multimodal data, leading to a dramatic boost in procedural planning accuracy.
Adaptive expert collaboration and holistic token learning can significantly boost performance in fine-grained multimodal visual analytics tasks like driver action recognition.
By pinpointing the causal origins of tool use, AttriGuard neutralizes indirect prompt injection attacks that can hijack LLM agents, even when faced with adversarial optimization.
LLMs struggle to understand nuanced values across languages, with accuracy dropping below 77% and varying by over 20% between languages, as revealed by the new X-Value benchmark.
Fine-tuning LLMs on datasets filtered at the token level, rather than the sentence level, can boost performance by up to 13.7%.
