144 citations · 865 across the 49 of their papers we have counts for
11 papers · 1 filter
InJePA: Intention-First Latent Planning with Coupled JEPA World Models for Visual Navigation
Siming Zhou, Bowen Ma, Ruiran Du +7
Visual navigation requires goal directed planning informed by predictions of environment dynamics. Representative navigation world model methods propose complete action candidates…
Hypernetwork-Parameterized Spatially Adaptive Neural Operators for PDE Learning
Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +7
Spatially heterogeneous partial differential equations (PDEs) exhibit location-dependent dynamics arising from variations in geometry and physical coefficients. Existing neural ope…
When and What to Teach: Budget-Aware Online Adaptation for Web Agents
Jianwei Zhang, Sihan Cao, Pengcheng Zheng +7
Web agents have achieved significant success in automating complex internet tasks but deploying them in real-world environments requires continuous online adaptation. Given that de…
Geometry-aware Incremental Neural Operator for Long-Horizon PDE prediction
Jiaquan Zhang, Shuxu Chen, Haifan Meng +6
Neural operators have shown strong potential for learning solution operators of partial differential equations (PDEs). However, long-horizon autoregressive prediction remains chall…
HERO: History-Enriched Rollout Training for Long-Horizon Autoregressive Neural Operators
Jiaquan Zhang, Shuxu Chen, Haifan Meng +6
Neural operators provide fast surrogates for time-dependent partial differential equations (PDEs) by applying a learned evolution operator recursively to its own predictions, but t…
TF-SNO: Time-Frequency Gated Spectral Neural Operators for Learning Non-Stationary Partial Differential Equations
Yitian Zhou, Chaoning Zhang, Zhenzhen Huang +8
Non-stationary partial differential equations (PDEs) arise throughout scientific computing, where the dominant frequency content and energy distribution can drift over time. While…
Autoregression-Free Neural Operators for Time-Dependent PDEs
Jiaquan Zhang, Caiyan Qin, Haoyu Bian +7
Neural operators learn mappings from function-dependent inputs to solutions, providing an effective framework for solving partial differential equations (PDEs). For time-dependent…
Efficient RAG with Intent-Aware Retrieval and Semantics-Preserving Chunking
Fachrina Dewi Puspitasari, Chaoning Zhang, Jiaquan Zhang +6
The demand for powerful instruction following and reasoning capability of large language models (LLMs) has promoted rapid development of retrieval-augmented generation (RAG). The R…
From Talking to Singing: A New Challenge for Audio-Visual Deepfake Detection
Ke Liu, Jiwei Wei, Wenyu Zhang +5
With rapid advances in audio-visual generative models, reliable forgery detection becomes increasingly critical. Existing methods for audio-visual deepfake detection typically rely…
CAP-CoT: Cycle Adversarial Prompt for Improving Chain of Thoughts in LLM Reasoning
Shuxu Chen, Yitian Zhou, Jiaquan Zhang +6
Chain-of-Thought (CoT) prompting has emerged as a simple and effective way to elicit step-by-step solutions from large language models (LLMs). However, CoT reasoning can be unstabl…
Topology-Aware Layer Pruning for Large Vision-Language Models
Pengcheng Zheng, Chaoning Zhang, Ya Wen +10
Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning, while recent extensions that incorporate visual inputs enable th…