9 papers
Toward Collective Model Intelligence: Characterizing and Coordinating Models
SinapisAI Team, Jian-Dong Liu, Qun Dai +27
Independently developed AI models accumulate diverse and complementary capabilities, but a growing model collection does not automatically realize Collective AI. Addressing this ga…
RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection
Tianyu Wang, Zhiyuan Ma, Qian Wang +3
Recent advancements in image generation have achieved impressive results in producing high-quality images. However, existing image generation models still generally struggle with a…
Investigating the Impact of Rationales for LLMs on Natural Language Understanding
Wenhang Shi, Shuqing Bian, Yiren Chen +5
Chain-of-thought (CoT) rationales, which provide step-by-step reasoning to derive final answers, benefit LLMs in both inference and training. Incorporating rationales, either by ge…
No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
Wenhang Shi, Yiren Chen, Shuqing Bian +6
Prompt engineering is crucial for leveraging the full potential of large language models (LLMs). While automatic prompt optimization offers a scalable alternative to costly manual…
FinSearchComp: Towards a Realistic, Expert-Level Evaluation of Financial Search and Reasoning
Liang Hu, Jianpeng Jiao, Jiashuo Liu +20
Search has emerged as core infrastructure for LLM-based agents and is widely viewed as critical on the path toward more general intelligence. Finance is a particularly demanding pr…
ST-Raptor: LLM-Powered Semi-Structured Table Question Answering
Zirui Tang, Boyu Niu, Xuanhe Zhou +6
Semi-structured tables, widely used in real-world applications (e.g., financial reports, medical records, transactional orders), often involve flexible and complex layouts (e.g., h…
Benchmarking Retrieval-Augmented Generation in Multi-Modal Contexts
Zhenghao Liu, Xingsheng Zhu, Tianshuo Zhou +5
With the rapid advancement of Multi-modal Large Language Models (MLLMs), their capability in understanding both images and text has greatly improved. However, their potential for l…
Joint Knowledge Editing for Information Enrichment and Probability Promotion
Wenhang Shi, Yiren Chen, Shuqing Bian +5
Knowledge stored in large language models requires timely updates to reflect the dynamic nature of real-world information. To update the knowledge, most knowledge editing methods f…
Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation
Yiyan Li, Haoyang Li, Zhao Pu +6
Knob tuning plays a crucial role in optimizing databases by adjusting knobs to enhance database performance. However, traditional tuning methods often follow a Try-Collect-Adjust a…