3 citations · 3 across the 4 of their papers we have counts for
5 papers · 1 filter
LatCom: Cross-Agent Latent Compression for Efficient Multi-Agent Collaboration
Shinan Zhang, Tao Zhang, Qihui Zhu +7
LLM-based multi-agent systems (MAS) increasingly use latent collaboration to avoid the information loss and repeated encoding-decoding overhead of natural-language communication. H…
Rethinking Stepwise Model Routing: A Cost-Efficient Table Reasoning Perspective
Shenghao Ye, Yuxiang Wang, Yu Guo +8
Large Reasoning Models (LRMs) achieve strong performance on table reasoning tasks but incur substantial inference cost due to long reasoning traces. Stepwise model routing mitigate…
Rethinking Table Pruning in TableQA: From Sequential Revisions to Gold Trajectory-Supervised Parallel Search
Yu Guo, Shenghao Ye, Shuangwu Chen +8
Table Question Answering (TableQA) benefits significantly from table pruning, which extracts compact sub-tables by eliminating redundant cells to streamline downstream reasoning. H…
When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables
Shenghao Ye, Yu Guo, Dong Jin +5
Table question answering (TableQA) is a fundamental task in natural language processing (NLP). The strong reasoning capabilities of large language models (LLMs) have brought signif…
SQLForge: Synthesizing Reliable and Diverse Data to Enhance Text-to-SQL Reasoning in LLMs
Yu Guo, Dong Jin, Shenghao Ye +3
Large Language models (LLMs) have demonstrated significant potential in text-to-SQL reasoning tasks, yet a substantial performance gap persists between existing open-source models…