3 papers
cs.CL2026
MeTHanol: Modularized Thinking Language Models with Intermediate Layer Thinking, Decoding and Bootstrapping Reasoning
Ningyuan Xi, Xiaoyu Wang, Yetao Wu +7
Current research efforts are focused on enhancing the thinking and reasoning capability of large language model (LLM) by prompting, data-driven emergence and inference-time computa…
cs.LG2025
M3-JEPA: Multimodal Alignment via Multi-gate MoE based on the Joint-Embedding Predictive Architecture
Hongyang Lei, Xiaolong Cheng, Qi Qin +8
Current multimodal learning strategies primarily optimize in the original token space. Such a framework is easy to incorporate with the backbone of pretrained language model, but m…
cs.CL2025
LaMsS: When Large Language Models Meet Self-Skepticism
Yetao Wu, Yihong Wang, Teng Chen +4
Hallucination is a major challenge for large language models (LLMs), preventing their further application in some fields. The skeptical thinking of humankind could be useful for LL…