2 citations · 3 across the 28 of their papers we have counts for
33 papers
GraphSkillAA: Attribution-Guided Skill-Graph Updating with Targeted Validation and Rollback
Ziqiao Shang, Ling-Yue Ge, Lan-Zhe Guo
External skills provide domain knowledge and procedures without updating model parameters, but flat collections obscure skill applicability, dependencies, and composition. Graphs o…
LookStep: Efficient Vision-Language Navigation with Linguistic Foresight and Event Driven Memory
Kun-Yang Yu, Yingzhe Li, Hongyu Xu +8
Vision-Language Navigation (VLN) requires an embodied agent to follow natural-language instructions in unseen environments. Recent progress has been largely driven by Multimodal La…
SymboLLM-FE: LLM-Accelerated Symbolic Regression for Automated Feature Engineering on Tabular Data
Zi-Jian Cheng, Zi-Yi Jia, Zhi Zhou +2
Tabular data, as a core data format in machine learning, often lacks the discriminative power needed for high-performance modeling due to insufficient feature informativeness. Auto…
STEGNav: Spatio-Temporal Event Graph Reasoning for Multimodal Lifelong Object Navigation
Yang Chen, Zhenyu Huang, Wenbo Fu +4
Multimodal lifelong navigation requires an agent to autonomously explore unseen environments while sequentially completing navigation tasks specified by object categories, language…
Can Agents Generalize to the Open World? Unveiling the Fragility of Static Training in Tool Use
Song-Lin Lv, Weiming Wu, Rui Zhu +2
While Large Language Model (LLM) agents demonstrate proficiency in static benchmarks, their deployment in real-world scenarios is hindered by the dynamic nature of user queries, to…
TriViewBench: Controlled Complexity Scaling for Multi-View Structural Reasoning in MLLMs
Yu-Yang Chen, Lan-Zhe Guo
Multimodal Large Language Models (MLLMs) demonstrate strong performance on standard visual question answering benchmarks, yet their scalability under controlled structural complexi…
On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
Zhi Zhou, Ming Yang, Shi-Yu Tian +3
Test-time adaptation (TTA) aims to adapt models to maintain reliable performance on non-stationary test streams without requiring labeled data. Despite its empirical success, the l…
Roles with Rails: Contract-Preserving Role Evolution in Multi-Agent Structured Reasoning
Ling-Yue Ge, Lan-Zhe Guo
Role-based LLM multi-agent systems need adaptive role pools, yet adapting such systems is not merely a matter of prompt optimization: roles often carry structural obligations, incl…
VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning
Zi-Yi Jia, Zi-Jian Cheng, Xin-Yue Zhang +4
Multi-model learning has attracted great attention in visual-text tasks. However, visual-tabular data, which plays a pivotal role in high-stakes domains like healthcare and industr…
STEPS: Selective On-Policy Self-Distillation for Reasoning
Jiaxuan Wang, Xuan Ouyang, Zhiyu Chen +4
On-policy self-distillation (OPSD) uses a model as its own teacher under privileged context, providing token-level supervision on the model's own reasoning trajectories. However, p…
LAST: Leveraging Tools as Hints to Enhance Spatial Reasoning for Multimodal Large Language Models
Shi-Yu Tian, Zhi Zhou, Kun-Yang Yu +5
Spatial reasoning is a cornerstone capability for intelligent systems to perceive and interact with the physical world. However, multimodal large language models (MLLMs) frequently…
A Progressive Visual-Logic-Aligned Framework for Ride-Hailing Adjudication
Weiming Wu, Zi-Jian Cheng, Jie Meng +5
The efficient adjudication of responsibility disputes is pivotal for maintaining marketplace fairness. However, the exponential surge in ride-hailing volume renders manual review i…
NeSy-Route: A Neuro-Symbolic Benchmark for Constrained Route Planning in Remote Sensing
Ming Yang, Zhi Zhou, Shi-Yu Tian +3
Remote sensing underpins crucial applications such as disaster relief and ecological field surveys, where systems must understand complex scenes and constraints and make reliable d…
MapTab: A Diagnostic Benchmark for Long-Horizon Multi-Criteria Multimodal Reasoning on Heterogeneous Topological Graphs
Ziqiao Shang, Ling-Yue Ge, Zian Xu +10
Systematically evaluating Multimodal Large Language Models (MLLMs) is essential for advancing Artificial General Intelligence (AGI). Yet existing benchmarks remain inadequate for r…
CaRLi-V: Camera-RADAR-LiDAR Point-Wise 3D Velocity Estimation
Landson Guo, Andres M. Diaz Aguilar, William Talbot +3
Accurate point-wise velocity estimation in 3D is crucial for robot interaction with non-rigid dynamic agents, enabling robust performance in path planning, collision avoidance, and…
A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning
Zhi Zhou, Yuhao Tan, Zenan Li +4
Test-time scaling seeks to improve the reasoning performance of large language models (LLMs) by adding computational resources. A prevalent approach within the field is sampling-ba…
FormalML: A Benchmark for Evaluating Formal Subgoal Completion in Machine Learning Theory
Xiao-Wen Yang, Zihao Zhang, Jianuo Cao +7
Large language models (LLMs) have recently demonstrated remarkable progress in formal theorem proving. Yet their ability to serve as practical assistants for mathematicians, fillin…
Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models
Xiao-Wen Yang, Jie-Jing Shao, Lan-Zhe Guo +5
Large Language Models (LLMs) have shown promising results across various tasks, yet their reasoning capabilities remain a fundamental challenge. Developing AI systems with strong r…
Data Selection for LLM Alignment Using Fine-Grained Preferences
Jia Zhang, Yao Liu, Chen-Xi Zhang +4
Large language models (LLMs) alignment aims to ensure that the behavior of LLMs meets human preferences. While collecting data from multiple fine-grained, aspect-specific preferenc…
Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning
Lin-Han Jia, Si-Yu Han, Wen-Chao Hu +5
The effectiveness of unlabeled data in Semi/Self-Supervised Learning (SSL) depends on appropriate assumptions for specific scenarios, thereby enabling the selection of beneficial u…
Realistic Evaluation of TabPFN v2 in Open Environments
Zi-Jian Cheng, Zi-Yi Jia, Zhi Zhou +2
Tabular data, owing to its ubiquitous presence in real-world domains, has garnered significant attention in machine learning research. While tree-based models have long dominated t…
TabularMath: Understanding Math Reasoning over Tables with Large Language Models
Shi-Yu Tian, Zhi Zhou, Wei Dong +5
Mathematical reasoning has long been a key benchmark for evaluating large language models. Although substantial progress has been made on math word problems, the need for reasoning…
NeSyGeo: A Neuro-Symbolic Framework for Multimodal Geometric Reasoning Data Generation
Weiming Wu, Jin Ye, Zi-kang Wang +3
Obtaining large-scale, high-quality reasoning data is crucial for improving the geometric reasoning capabilities of multi-modal large language models (MLLMs). However, existing dat…
Detecting Scarce and Sparse Anomalous: Solving Dual Imbalance in Multi-Instance Learning
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou +3
In real-world applications, it is highly challenging to detect anomalous samples with extremely sparse anomalies, as they are highly similar to and thus easily confused with normal…