1 citations · 1 across the 5 of their papers we have counts for
6 papers
Is This Evidence Decision-Critical? Learning to Verify Rule-Governed Decisions
Haoyang Zhang, Jianpeng Zhao, Qi Hao +1
Rule-based reasoning, as in eligibility checks and contract reviews, requires language models to assess evidence against individual conditions and combine their judgments under exp…
Large Language Models as Virtual Survey Respondents: Evaluating Sociodemographic Response Generation
Jianpeng Zhao, Chenyu Yuan, Weiming Luo +6
Questionnaire-based surveys are foundational to social science research and public policymaking, yet traditional survey methods remain costly, time-consuming, and often limited in…
Mut4All: Fuzzing Compilers via LLM-Synthesized Mutators Learned from Bug Reports
Bo Wang, Pengyang Wang, Chong Chen +9
Mutation-based fuzzing is effective for uncovering compiler bugs, but designing high-quality mutators for modern languages with complex constructs (e.g., templates, macros) remains…
SC: Speculative Sampling with Syntactic and Semantic Coherence for Efficient Inference of Large Language Models
Tao He, Guang Huang, Yu Yang +5
Large language models (LLMs) exhibit remarkable reasoning capabilities across diverse downstream tasks. However, their autoregressive nature leads to substantial inference latency,…
Out-of-Distribution Graph Models Merging
Yidi Wang, Ziyue Qiao, Jiawei Gu +4
This paper studies a novel problem of out-of-distribution graph models merging, which aims to construct a generalized model from multiple graph models pre-trained on different doma…
Disentangled Multi-span Evolutionary Network against Temporal Knowledge Graph Reasoning
Hao Dong, Ziyue Qiao, Zhiyuan Ning +4
Temporal Knowledge Graphs (TKGs), as an extension of static Knowledge Graphs (KGs), incorporate the temporal feature to express the transience of knowledge by describing when facts…