3 papers
cs.LG2026
On Surprising Effectiveness of Masking Updates in Adaptive Optimizers
Taejong Joo, Wenhan Xia, Cheolmin Kim +2
Training large language models (LLMs) relies almost exclusively on dense adaptive optimizers with increasingly sophisticated preconditioners. We challenge this by showing that rand…
cs.CL2025
Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?
Chengwei Qin, Wenhan Xia, Tan Wang +5
Analogical reasoning is a unique ability of humans to address unfamiliar challenges by transferring strategies from relevant past experiences. One key finding in psychology is that…
cs.CL2025
Beyond Output Matching: Bidirectional Alignment for Enhanced In-Context Learning
Chengwei Qin, Wenhan Xia, Fangkai Jiao +5
Large language models (LLMs) have shown impressive few-shot generalization on many tasks via in-context learning (ICL). Despite their success in showing such emergent abilities, th…