Recent developments have demonstrated the efficacy of enhancing the reliability and reasoning ability of Large Language Models (LLMs) through the integration of Knowledge Graphs (KGs). However, previous works have not fully considered the challenges present in expert domains, including the prevalence of professional te...
Shuo-Ling Liu, Hui Wu, Kun Yi et al.· IEEE Transactions on Knowled...· 0 citations
Large language models (LLMs) provide limited support for sign language interaction. Unifying sign language translation (SLT) and generation (SLG) to enable sign language as both input and output can reduce switching between separate models during sign-text interaction. We present SignGPT, a unified, pose-based framewor...
Rong-Hui Li, Jun Dong, Zhongyuan Hu et al.· 0 citations
Since the advent of knowledge distillation, KL divergence has been the standard loss in distillation. Recently, on-policy distillation (OPD) has emerged as an efficient post-training paradigm for LLMs. As a distillation method, OPD naturally inherits KL divergence as its standard loss. However, in this work, we find th...
Wen-Ze Lin, Ji-Yuan Long, Jia-Le Zhao et al.· 0 citations
TradeLens is introduced, a trace-grounded diagnostic toolkit for evaluating agentic trading systems from their trading records, runtime traces, and deployment configurations, which reframe the evaluation of LLM-based trading agents from capability-centric performance ranking to trace-grounded diagnosis of intelligence-...
Qiqi Duan, Changlun Li, Chen Wang et al.· arXiv.org· 0 citations
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