5 papers
Stepwise Reasoning Enhancement for LLMs via External Subgraph Generation
Xin Zhang, Yang Cao, Baoxing Wu +2
Large language models have shown strong performance in natural language generation and downstream reasoning tasks, but they still struggle with logical consistency, factual groundi…
SGR: A Stepwise Reasoning Framework for LLMs with External Subgraph Generation
Xin Zhang, Yang Cao, Baoxing Wu +2
Large Language Models (LLMs) have demonstrated strong capabilities across diverse NLP applications, such as translation, text generation, and question answering. Nevertheless, they…
SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
Haiwen Diao, Penghao Wu, Hanming Deng +55
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…
CoTJudger: A Graph-Driven Framework for Automatic Evaluation of Chain-of-Thought Efficiency and Redundancy in LRMs
Siyi Li, Jiajun Shi, Shiwen Ni +9
Large Reasoning Models (LRMs) have demonstrated strong performance by producing extended Chain-of-Thought (CoT) traces before answering. However, this paradigm often induces over-r…
A Stepwise-Enhanced Reasoning Framework for Large Language Models Based on External Subgraph Generation
Xin Zhang, Yang Cao, Baoxing Wu +3
Large Language Models (LLMs) have achieved strong performance across a wide range of natural language processing tasks in recent years, including machine translation, text generati…