6 papers
DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail
He Liu, Changtao Miao, Xinjie Yang +12
Large language models deployed in open-world applications require safety guardrails that are both robust to complex risks and efficient enough for low-latency runtime moderation. E…
Visual-Seeker: Towards Visual-Native Multimodal Agentic Search via Active Visual Reasoning
Zhengbo Zhang, Changtao Miao, Jinbo Su +10
Multimodal large language models (MLLMs) have demonstrated impressive capabilities in many visual tasks, but they often struggle with factual grounding when confronted with complex…
ViRC: Enhancing Visual Interleaved Mathematical CoT with Reason Chunking
Lihong Wang, Liangqi Li, Weiwei Feng +6
CoT has significantly enhanced the reasoning ability of LLMs while it faces challenges when extended to multimodal domains, particularly in mathematical tasks. Existing MLLMs typic…
Beyond Next-Token Alignment: Distilling Multimodal Large Language Models via Token Interactions
Lin Chen, Xiaoke Zhao, Kun Ding +9
Multimodal Large Language Models (MLLMs) demonstrate impressive cross-modal capabilities, yet their substantial size poses significant deployment challenges. Knowledge distillation…
Agentar-DeepFinance-100K: A Large-Scale Financial Dataset via Systematic Chain-of-Thought Synthesis Optimization
Xiaoke Zhao, Zhaowen Zhou, Lin Chen +12
Recent advancements in large language models (LLMs) have demonstrated remarkable general reasoning capabilities, holding significant potential for applications in the financial dom…
Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning
Yanjun Zheng, Xiyang Du, Longfei Liao +10
Large Language Models (LLMs) exhibit considerable promise in financial applications; however, prevailing models frequently demonstrate limitations when confronted with scenarios th…