10 papers
SCONE: A Practical, Constraint-Aware Plug-in for Latent Encoding in Learned DNA Storage
Cihan Ruan, Lebin Zhou, Rongduo Han +6
DNA storage has matured from concept to practical stage, yet its integration with neural compression pipelines remains inefficient. Early DNA encoders applied redundancy-heavy cons…
Socratic-Geo: Synthetic Data Generation and Geometric Reasoning via Multi-Agent Interaction
Zhengbo Jiao, Shaobo Wang, Zifan Zhang +4
Multimodal Large Language Models (MLLMs) have significantly advanced vision-language understanding. However, even state-of-the-art models struggle with geometric reasoning, reveali…
Agentic Proposing: Enhancing Large Language Model Reasoning via Compositional Skill Synthesis
Zhengbo Jiao, Shaobo Wang, Zifan Zhang +5
Advancing complex reasoning in large language models relies on high-quality, verifiable datasets, yet human annotation remains cost-prohibitive and difficult to scale. Current synt…
PLawBench: A Rubric-Based Benchmark for Evaluating LLMs in Real-World Legal Practice
Yuzhen Shi, Huanghai Liu, Yiran Hu +27
As large language models (LLMs) are increasingly applied to legal domain-specific tasks, evaluating their ability to perform legal work in real-world settings has become essential.…
Logics-STEM: Empowering LLM Reasoning via Failure-Driven Post-Training and Document Knowledge Enhancement
Mingyu Xu, Cheng Fang, Keyue Jiang +16
We present Logics-STEM, a state-of-the-art reasoning model fine-tuned on Logics-STEM-SFT-Dataset, a high-quality and diverse dataset at 10M scale that represents one of the largest…
LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios
Bingxi Zhao, Lin Geng Foo, Ping Hu +3
Recent advances in the intrinsic reasoning capabilities of large language models (LLMs) have given rise to LLM-based agent systems that exhibit near-human performance on a variety…