1 citations · 1 across the 17 of their papers we have counts for
20 papers
Towards Physics-Faithful Generation of Scientific Diagrams
Minghui Zhang, Jinxin Shi, Yifan Chang +12
Text-to-image generation has reached photorealistic quality, yet state-of-the-art systems remain unreliable at producing scientific diagrams, whose value depends not on appearance…
Claim-Level Reliability Assessment for Efficient Test-Time Reasoning
Sen Xu, Wei Wang, Shixi Liu +5
We propose claim-level falsification as a principle for test-time scaling and instantiate it through Claim-Level Reliability Assessment (CLR), a training-free framework that reallo…
TransMem: Transforming Hidden States into Memory for Large Language Models
Haodong Lei, Junming Liu, Yirong Chen +4
Large language model (LLM) agents increasingly operate over long interaction histories, where effective reasoning requires identifying and exploiting task-relevant evidence distrib…
SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning
Cheng Tang, Junzhi Ning, Min Cen +9
Reinforcement learning with verifiable rewards (RLVR) drives multimodal reasoning, but answer-level correctness does not guarantee that a vision-language model grounds its predicti…
A First-Principles Derivation of LLM Policy Optimization: From Expected Reward to GRPO and Its Structural Extensions
Jianghan Shen, Siqi Luo, Yue Li +9
Policy gradient algorithms for language models optimize the same objective , which has exactly two factors: the trajectory probability $p_θ(…
VibeThinker-3B: Exploring the Frontier of Verifiable Reasoning in Small Language Models
Sen Xu, Shixi Liu, Wei Wang +6
This technical report introduces VibeThinker-3B, a compact dense model with 3B parameters developed to investigate how far verifiable reasoning can be pushed within a strictly smal…
OmniTraffic: A Controllable Generation Pipeline and Benchmark for Spatio-Temporal Traffic Reasoning
Maonan Wang, Zhengyan Huang, Kemou Jiang +13
Traffic scene understanding requires models to reason beyond object recognition, including lane topology, multi-view geometry, temporal evolution, and signal-phase semantics. Howev…
Self-Evolving Spatial Reasoning in Vision Language Models via Geometric Logic Consistency
Junming Liu, Yuqi Li, Yifei Sun +6
Vision-Language Models (VLMs) have made striking progress, yet their spatial reasoning remains fragile. Models that answer an original input correctly can still fail under valid tr…
MemCoT: Test-Time Scaling through Memory-Driven Chain-of-Thought
Haodong Lei, Junming Liu, Yirong Chen +2
Large Language Models (LLMs) still suffer from severe hallucinations and catastrophic forgetting during causal reasoning over massive, fragmented long contexts. Existing memory mec…
CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG
Jianghan Shen, Siqi Luo, Xinyu Cheng +6
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for training agentic retrieval-augmented generation (RAG) systems from outcome-only superv…
MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline
Jiyao Liu, Jianghan Shen, Sida Song +19
Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medicine, developing clinical guid…
Hierarchical Memory Orchestration for Personalized Persistent Agents
Junming Liu, Yifei Sun, Weihua Cheng +4
While long-term memory is essential for intelligent agents to maintain consistent historical awareness, the accumulation of extensive interaction data often leads to performance bo…
MemVerse: Multimodal Memory for Lifelong Learning Agents
Junming Liu, Yifei Sun, Weihua Cheng +11
Despite rapid progress in large-scale language and vision models, AI agents still suffer from a fundamental limitation: they cannot remember. Without reliable memory, agents catast…
ReBrain: Brain MRI Reconstruction from Sparse CT Slice via Retrieval-Augmented Diffusion
Junming Liu, Yifei Sun, Weihua Cheng +4
Magnetic Resonance Imaging (MRI) plays a crucial role in brain disease diagnosis, but it is not always feasible for certain patients due to physical or clinical constraints. Recent…
MGA: Memory-Driven GUI Agent for Observation-Centric Interaction
Weihua Cheng, Junming Liu, Yifei Sun +3
Multimodal Large Language Models (MLLMs) have significantly advanced GUI agents, yet long-horizon automation remains constrained by two critical bottlenecks: context overload from…
TimeMKG: Knowledge-Infused Causal Reasoning for Multivariate Time Series Modeling
Yifei Sun, Junming Liu, Yirong Chen +2
Multivariate time series data typically comprises two distinct modalities: variable semantics and sampled numerical observations. Traditional time series models treat variables as…
From Ranking to Selection: A Simple but Efficient Dynamic Passage Selector for Retrieval Augmented Generation
Siyuan Meng, Junming Liu, Yirong Chen +5
Retrieval-augmented generation (RAG) systems are often bottlenecked by their reranking modules, which typically score passages independently and select a fixed Top-K size. This app…
Mosaic: Data-Free Knowledge Distillation via Mixture-of-Experts for Heterogeneous Distributed Environments
Junming Liu, Yanting Gao, Yuqi Li +6
Federated Learning (FL) is a decentralized machine learning paradigm that enables clients to collaboratively train models while preserving data privacy. However, the coexistence of…
FedRecon: Missing Modality Reconstruction in Heterogeneous Distributed Environments
Junming Liu, Yanting Gao, Yifei Sun +4
Multimodal data are often incomplete and exhibit Non-Independent and Identically Distributed (Non-IID) characteristics in real-world scenarios. These inherent limitations lead to b…
Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning
Junming Liu, Siyuan Meng, Yanting Gao +7
Multimodal reasoning in Large Language Models (LLMs) struggles with incomplete knowledge and hallucination artifacts, challenges that textual Knowledge Graphs (KGs) only partially…