8 papers
Seeing Is No Longer Believing: Frontier Image Generation Models, Synthetic Visual Evidence, and Real-World Risk
Shuai Wu, Xue Li, Yanna Feng +3
Frontier image generation has moved from artistic synthesis toward synthetic visual evidence. Systems such as GPT Image 2, Nano Banana Pro, Nano Banana 2, Nano Banana 2 Lite, Grok…
The Rise of Verbal Tics in Large Language Models: A Systematic Analysis Across Frontier Models
Shuai Wu, Xue Li, Yanna Feng +3
As Large Language Models (LLMs) continue to evolve through alignment techniques such as Reinforcement Learning from Human Feedback (RLHF) and Constitutional AI, a growing and incre…
Council Mode: A Heterogeneous Multi-Agent Consensus Framework for Reducing LLM Hallucination and Bias
Shuai Wu, Xue Li, Yanna Feng +3
Large Language Models (LLMs) have demonstrated advanced capabilities but often suffer from factual inaccuracies (hallucinations) and systematic biases. These issues, sometimes ampl…
Efficient Multilingual Reasoning Transfer via Progressive Code-Switching
Zhijun Wang, Junxiao Liu, Hao Zhou +3
Large reasoning models (LRMs) have achieved strong reasoning capabilities in English, yet their performance degrades significantly when required to reason in other languages. A nat…
A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM Integration into Upcycled MoE
Hao Zhou, Tianhao Li, Zhijun Wang +6
Expanding Large Language Models~(LLMs) to new languages is a costly endeavor, demanding extensive Continued Pre-Training~(CPT) and data-intensive alignment. While recent data-free…
R3S: Refining and Recovering Reinforcement Signals for Multilingual Understanding and Reasoning
Junxiao Liu, Zhijun Wang, Yixiao Li +6
Large reasoning models often default to English reasoning when processing non-English questions, yet their performance drops substantially when reasoning in the question language.…