1 citations · 3 across the 18 of their papers we have counts for
21 papers
EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research
Haolin Yang, Zhiqiang Qian, Chutian Chen +7
Automated alpha factor discovery is critical for modern quantitative research. While large language models (LLMs) have increasingly been integrated into quantitative workflows, exi…
RS-HyRe-R1: A Hybrid Reward Mechanism to Overcome Perceptual Inertia for Remote Sensing Images Understanding
Gaozhi Zhou, Hu He, Peng Shen +8
Reinforcement learning (RL) post-training substantially improves remote sensing vision-language models (RS-VLMs). However, when handling complex remote sensing imagery (RSI) requir…
FarmMind: Reasoning-Query-Driven Dynamic Segmentation for Farmland Remote Sensing Images
Haiyang Wu, Weiliang Mu, Jipeng Zhang +4
Existing methods for farmland remote sensing image (FRSI) segmentation generally follow a static segmentation paradigm, where analysis relies solely on the limited information cont…
MMedExpert-R1: Strengthening Multimodal Medical Reasoning via Domain-Specific Adaptation and Clinical Guideline Reinforcement
Meidan Ding, Jipeng Zhang, Wenxuan Wang +4
Medical Vision-Language Models (MedVLMs) excel at perception tasks but struggle with complex clinical reasoning required in real-world scenarios. While reinforcement learning (RL)…
Layer-Order Inversion: Rethinking Latent Multi-Hop Reasoning in Large Language Models
Xukai Liu, Ye Liu, Jipeng Zhang +3
Large language models (LLMs) perform well on multi-hop reasoning, yet how they internally compose multiple facts remains unclear. Recent work proposes \emph{hop-aligned circuit hyp…
MarineEval: Assessing the Marine Intelligence of Vision-Language Models
YuK-Kwan Wong, Tuan-An To, Jipeng Zhang +2
We have witnessed promising progress led by large language models (LLMs) and further vision language models (VLMs) in handling various queries as a general-purpose assistant. VLMs,…
LongVideoAgent: Multi-Agent Reasoning with Long Videos
Runtao Liu, Ziyi Liu, Jiaqi Tang +4
Recent advances in multimodal LLMs and systems that use tools for long-video QA point to the promise of reasoning over hour-long episodes. However, many methods still compress cont…
Skin-R1: Clinical Knowledge-Guided Dermatological Diagnosis Using Vision-Language Models
Zehao Liu, Weijieying Ren, Jipeng Zhang +4
Vision--language models (VLMs) have recently shown promise for assisting clinical reasoning in dermatological diagnosis. However, their trustworthiness and clinical utility remain…
RIDE: Difficulty Evolving Perturbation with Item Response Theory for Mathematical Reasoning
Xinyuan Li, Murong Xu, Wenbiao Tao +4
Large language models (LLMs) achieve high performance on mathematical reasoning, but these results can be inflated by training data leakage or superficial pattern matching rather t…
MARS-SQL: A multi-agent reinforcement learning framework for Text-to-SQL
Haolin Yang, Jipeng Zhang, Zhitao He +2
Large Language Models (LLMs) often struggle with the precise logic and schema alignment required for complex Text-to-SQL tasks. While current methods rely heavily on static prompti…
Pointing to a Llama and Call it a Camel: On the Sycophancy of Multimodal Large Language Models
Renjie Pi, Kehao Miao, Li Peihang +4
Multimodal large language models (MLLMs) have demonstrated extraordinary capabilities in conducting conversations based on image inputs. However, we observe that MLLMs exhibit a pr…
Med-RewardBench: Benchmarking Reward Models and Judges for Medical Multimodal Large Language Models
Meidan Ding, Jipeng Zhang, Wenxuan Wang +6
Multimodal large language models (MLLMs) hold significant potential in medical applications, including disease diagnosis and clinical decision-making. However, these tasks require…
Remote Sensing Image Intelligent Interpretation with the Language-Centered Perspective: Principles, Methods and Challenges
Haifeng Li, Wang Guo, Haiyang Wu +6
The mainstream paradigm of remote sensing image interpretation has long been dominated by vision-centered models, which rely on visual features for semantic understanding. However,…
VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training
Jipeng Zhang, Kehao Miao, Renjie Pi +4
Reinforcement Fine-Tuning (RFT) with verifiable rewards has advanced large language models but remains underexplored for Vision-Language (VL) models. The Vision-Language Reward Mod…
LegalReasoner: Step-wised Verification-Correction for Legal Judgment Reasoning
Weijie Shi, Han Zhu, Jiaming Ji +7
Legal judgment prediction (LJP) aims to function as a judge by making final rulings based on case claims and facts, which plays a vital role in the judicial domain for supporting c…
Benchmarking Multi-National Value Alignment for Large Language Models
Weijie Shi, Chengyi Ju, Chengzhong Liu +8
Do Large Language Models (LLMs) hold positions that conflict with your country's values? Occasionally they do! However, existing works primarily focus on ethical reviews, failing t…
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training
Weijie Shi, Jipeng Zhang, Yaguang Wu +8
Large language models (LLMs) are commonly trained on multi-domain datasets, where domain sampling strategies significantly impact model performance due to varying domain importance…
WSI-LLaVA: A Multimodal Large Language Model for Whole Slide Image
Yuci Liang, Xinheng Lyu, Wenting Chen +8
Recent advancements in computational pathology have produced patch-level Multi-modal Large Language Models (MLLMs), but these models are limited by their inability to analyze whole…
The Instinctive Bias: Spurious Images lead to Illusion in MLLMs
Tianyang Han, Qing Lian, Rui Pan +5
Large language models (LLMs) have recently experienced remarkable progress, where the advent of multi-modal large language models (MLLMs) has endowed LLMs with visual capabilities,…
PipeNet: Question Answering with Semantic Pruning over Knowledge Graphs
Ying Su, Jipeng Zhang, Yangqiu Song +1
It is well acknowledged that incorporating explicit knowledge graphs (KGs) can benefit question answering. Existing approaches typically follow a grounding-reasoning pipeline in wh…
MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance
Renjie Pi, Tianyang Han, Jianshu Zhang +6
The deployment of multimodal large language models (MLLMs) has brought forth a unique vulnerability: susceptibility to malicious attacks through visual inputs. This paper investiga…