23 citations · 47 across the 20 of their papers we have counts for
20 papers
EpochX: Building the Infrastructure for an Emergent Agent Civilization
Huacan Wang, Chaofa Yuan, Xialie Zhuang +15
General-purpose technologies reshape economies less by improving individual tools than by enabling new ways to organize production and coordination. We believe AI agents are approa…
Controlled Self-Evolution for Algorithmic Code Optimization
Tu Hu, Ronghao Chen, Shuo Zhang +9
Self-evolution methods enhance code generation through iterative "generate-verify-refine" cycles, yet existing approaches suffer from low exploration efficiency, failing to discove…
Spider-Sense: Intrinsic Risk Sensing for Efficient Agent Defense with Hierarchical Adaptive Screening
Zhenxiong Yu, Zhi Yang, Zhiheng Jin +19
As large language models (LLMs) evolve into autonomous agents, their real-world applicability has expanded significantly, accompanied by new security challenges. Most existing agen…
QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining
Jun Han, Shuo Zhang, Wei Li +14
Financial markets are noisy and non-stationary, making alpha mining highly sensitive to backtest noise and regime shifts. While recent agentic frameworks improve automation, they o…
KG-o1: Enhancing Multi-hop Question Answering in Large Language Models via Knowledge Graph Integration
Nan Wang, Yongqi Fan, yansha zhu +6
Large Language Models (LLMs) face challenges in knowledge-intensive reasoning tasks like classic multi-hop question and answering, which involves reasoning across multiple facts. T…
I2CR: Intra- and Inter-modal Collaborative Reflections for Multimodal Entity Linking
Ziyan Liu, Junwen Li, Kaiwen Li +6
Multimodal entity linking plays a crucial role in a wide range of applications. Recent advances in large language model-based methods have become the dominant paradigm for this tas…
DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models
Luolin Xiong, Haofen Wang, Xi Chen +7
DeepSeek, a Chinese Artificial Intelligence (AI) startup, has released their V3 and R1 series models, which attracted global attention due to their low cost, high performance, and…
MinosEval: Distinguishing Factoid and Non-Factoid for Tailored Open-Ended QA Evaluation with LLMs
Yongqi Fan, Yating Wang, Guandong Wang +4
Open-ended question answering (QA) is a key task for evaluating the capabilities of large language models (LLMs). Compared to closed-ended QA, it demands longer answer statements,…
Can Multimodal Large Language Models Understand Spatial Relations?
Jingping Liu, Ziyan Liu, Zhedong Cen +5
Spatial relation reasoning is a crucial task for multimodal large language models (MLLMs) to understand the objective world. However, current benchmarks have issues like relying on…
CMQCIC-Bench: A Chinese Benchmark for Evaluating Large Language Models in Medical Quality Control Indicator Calculation
Guangya Yu, Yanhao Li, Zongying Jiang +9
Medical quality control indicators are essential to assess the qualifications of healthcare institutions for medical services. With the impressive performance of large language mod…
MSDiagnosis: A Benchmark for Evaluating Large Language Models in Multi-Step Clinical Diagnosis
Ruihui Hou, Shencheng Chen, Yongqi Fan +5
Clinical diagnosis is critical in medical practice, typically requiring a continuous and evolving process that includes primary diagnosis, differential diagnosis, and final diagnos…
Negation Triplet Extraction with Syntactic Dependency and Semantic Consistency
Yuchen Shi, Deqing Yang, Jingping Liu +3
Previous works of negation understanding mainly focus on negation cue detection and scope resolution, without identifying negation subject which is also significant to the downstre…
Exploiting Duality in Open Information Extraction with Predicate Prompt
Zhen Chen, Jingping Liu, Deqing Yang +5
Open information extraction (OpenIE) aims to extract the schema-free triplets in the form of (\emph{subject}, \emph{predicate}, \emph{object}) from a given sentence. Compared with…
A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics
Xiangru Zhu, Penglei Sun, Chengyu Wang +4
Text-to-image (T2I) synthesis has recently achieved significant advancements. However, challenges remain in the model's compositionality, which is the ability to create new combina…
AF Adapter: Continual Pretraining for Building Chinese Biomedical Language Model
Yongyu Yan, Kui Xue, Xiaoming Shi +3
Continual pretraining is a popular way of building a domain-specific pretrained language model from a general-domain language model. In spite of its high efficiency, continual pret…
FL-Tuning: Layer Tuning for Feed-Forward Network in Transformer
Jingping Liu, Yuqiu Song, Kui Xue +6
Prompt tuning is an emerging way of adapting pre-trained language models to downstream tasks. However, the existing studies are mainly to add prompts to the input sequence. This wa…
Rule Mining over Knowledge Graphs via Reinforcement Learning
Lihan Chen, Sihang Jiang, Jingping Liu +6
Knowledge graphs (KGs) are an important source repository for a wide range of applications and rule mining from KGs recently attracts wide research interest in the KG-related resea…
Revisiting the Negative Data of Distantly Supervised Relation Extraction
Chenhao Xie, Jiaqing Liang, Jingping Liu +3
Distantly supervision automatically generates plenty of training samples for relation extraction. However, it also incurs two major problems: noisy labels and imbalanced training d…
CN-Probase: A Data-driven Approach for Large-scale Chinese Taxonomy Construction
Jindong Chen, Ao Wang, Jiangjie Chen +5
Taxonomies play an important role in machine intelligence. However, most well-known taxonomies are in English, and non-English taxonomies, especially Chinese ones, are still very r…
Deep Short Text Classification with Knowledge Powered Attention
Jindong Chen, Yizhou Hu, Jingping Liu +2
Short text classification is one of important tasks in Natural Language Processing (NLP). Unlike paragraphs or documents, short texts are more ambiguous since they have not enough…