Researchers from Japan have developed a method to automatically generate diverse personas for user simulators in interview dialogue systems. This can ...
Researchers have developed a method to improve financial named entity recognition (NER) under domain shift. They tested their approach on three types ...
Researchers propose a framework for evaluating the memory commitment of large language models (LLMs) in various scenarios. They present a dataset call...
Researchers have developed a new framework called LifeMem to improve the performance of large language models (LLMs) in social simulation. Current met...
Researchers have developed ReCache, a framework that improves the efficiency of large language models (LLMs) by reducing their computational and memor...
Researchers have found that compressing large language models (LLMs) can lead to uneven effects on their performance. Specifically, compression tends ...
Researchers from the University of California, Berkeley, have published a paper proposing a new approach to training multimodal large language models....
Researchers have created a sandbox called Thinkingbox to test the reliability of artificial agents in complex business workflows. The sandbox allows f...
Researchers have introduced PersonalBench, a benchmark for evaluating personalized text generation in large language models (LLMs). The benchmark asse...
Researchers have developed FlashPrefill V2, an improved version of their previous work on long-context modeling for Large Language Models. The new sys...
Researchers have created SWE-bench Science, a benchmark to evaluate coding agents' ability to resolve engineering tasks in science. The benchmark cons...
Researchers from Bin Zhu, Yi Xie, and Yanghui Rao have proposed a method to design judge panels for Large Language Models (LLMs). The approach, called...