6 citations · 8 across the 37 of their papers we have counts for
42 papers
T-WLA: Bridging Slow Vision and Fast Touch
Kaichen Zhou, Yuzhen Chen, Hannah Yao +14
In contact-rich manipulation, contact conditions can change before a visual policy updates its action plan. Recomputing the plan through the visual policy adds latency, while tacti…
REWIND: Uncertainty-Guided Trajectory Repair for Test-Time Reasoning
Yi Ding, Mengyu Wang, Min Zhou +1
An early mistake in the generated reasoning can constrain all subsequent reasoning. Repeated-generation methods, like MCMC-based approaches, attempt to improve output quality by sa…
Focus Where It Counts: A Salience-Driven Vision-Language Model for Low Vision Assistance
Jiazhao Liang, Hao Huang, Shuaihang Yuan +8
Vision-language models (VLMs) are rapidly progressing and offer promising capabilities for assistive technologies supporting persons with blindness or low vision. However, existing…
Graph-Based Pseudo-multimodal Contrastive Learning for 12-Lead ECG Representations
Mengyu Wang, Kozo Okada, Takafumi Goto +4
12-lead electrocardiogram (ECG) is a standard, non-invasive examination widely used for diagnosing coronary artery disease, where clinical interpretation relies on comparing wavefo…
StateFlow: Building, Evolving, and Accessing 3D World States for Previsualization
Yuyang Yin, Zixiang Li, Longxuan Deng +11
Previsualization is an intermediate layer between ideas and production in film, games, architecture, and urban design. It lets creators iteratively refine scenes, actions, cameras,…
StructGen: Disambiguating Multi-Reference Image Generation via Structured Context Modeling
Jianing Peng, Mengyu Wang, Henghui Ding +6
Multi-reference image generation aims to synthesize images by integrating attributes from multiple reference images under textual instructions. As the number of references increase…
Rethinking One-Step Image Editing through ChordEdit: Reproduction, Simplification, and New Insights
Minghan Li, Jeremy Moebel, Mengyu Wang
One-step image editing is important for making text-guided editing fast, practical, and easy to deploy, but its underlying mechanism is still not fully understood. We revisit Chord…
GeoWorld-VLM: Geometry from World Models for Vision-Language Models
Renjie Gu, Kaichen Zhou, Yan Luo +1
Modern Vision-Language Models (VLMs) achieve strong semantic recognition, yet remain brittle on elementary spatial relations such as left of, on, behind, and between. One cause of…
Beyond Motion Primitives: Behavioral Activity Recognition from Head-Mounted IMU
Chung-Ta Huang, Leopold Das, Jeffrey Zhou +10
AR smart glasses need continuous behavioral context to offer proactive assistance, yet their most practical always-on sensor, the head-mounted Inertial Measurement Unit (IMU), dete…
VAGS: Velocity Adaptive Guidance Scale for Image Editing and Generation
Yan Luo, Ahmadou Aidara, Jingyi Lu +3
Classifier-free guidance (CFG) is the primary control over how strongly text semantics move a flow-based sampler, yet standard practice holds its scale fixed across the entire ODE…
Summoning the Oracle to Slay It: Mitigating Look-Ahead Bias in Financial Backtesting with Large Language Models
Weixian Waylon Li, Mengyu Wang, Tiejun Ma
Backtesting large language models (LLMs) on historical financial data is unreliable when their pre-training data include the evaluated events. An LLM trained in 2024 may already en…
GEM-4D: Geometry-Enhanced Video World Models for Robot Manipulation
Kaichen Zhou, Yuzhen Chen, Fangneng Zhan +8
Video world models can generate realistic futures from a single instruction, but they often fail to track the same physical points consistently across time. As a result, the genera…
Stream3D: Sequential Multi-View 3D Generation via Evidential Memory
Kaichen Zhou, Zeyang Bai, Xinhai Chang +3
View-conditioned 3D generators such as SAM 3D, TRELLIS, and Hunyuan3D produce high-quality object reconstructions from a single view, but real-world visual observation often arrive…
Self Knowledge Re-expression: A Fully Local Method for Adapting LLMs to Tasks Using Intrinsic Knowledge
Mengyu Wang, Xiaoying Zhi, Zhiyi Li +4
While the next-token prediction (NTP) paradigm enables large language models (LLMs) to express their intrinsic knowledge, its sequential nature constrains performance on specialize…
MedConclusion: A Benchmark for Biomedical Conclusion Generation from Structured Abstracts
Weiyue Li, Ruizhi Qian, Yi Li +5
Large language models (LLMs) are widely explored for reasoning-intensive research tasks, yet resources for testing whether they can infer scientific conclusions from structured bio…
Individual and Combined Effects of English as a Second Language and Typos on LLM Performance
Serena Liu, Yutong Yang, Prisha Sheth +9
Large language models (LLMs) are used globally, and because much of their training data is in English, they typically perform best on English inputs. As a result, many non-native E…
Do Emotions in Prompts Matter? Effects of Emotional Framing on Large Language Models
Minda Zhao, Yutong Yang, Chufei Peng +5
Emotional tone is pervasive in human communication, yet its influence on large language model (LLM) behaviour remains unclear. Here, we examine how first-person emotional framing i…
TrustTrade: Human-Inspired Selective Consensus Reduces Decision Uncertainty in LLM Trading Agents
Minghan Li, Rachel Gonsalves, Weiyue Li +2
Large language models (LLMs) are increasingly deployed as autonomous agents in financial trading. However, they often exhibit a hazardous behavioral bias that we term uniform trust…
Setting-Matched and Semantics-Scaled Benchmarking of One-Step Generative Models Against Multistep Diffusion and Flow Models
Advaith Ravishankar, Serena Liu, Mingyang Wang +11
State-of-the-art text-to-image models produce high-quality images, but inference remains expensive as generation requires several sequential ODE or denoising steps. Native one-step…
Single-Slice-to-3D Reconstruction in Medical Imaging and Natural Objects: A Comparative Benchmark with SAM 3D
Yan Luo, Advaith Ravishankar, Serena Liu +2
While three-dimensional imaging is essential for clinical diagnosis, its high cost and long wait times have motivated the use of image-to-3D foundation models to infer volume from…
Look-Ahead and Look-Back Flows: Training-Free Image Generation with Trajectory Smoothing
Yan Luo, Henry Huang, Todd Y. Zhou +1
Recent advances have reformulated diffusion models as deterministic ordinary differential equations (ODEs) through the framework of flow matching, providing a unified formulation f…
TrailBlazer: History-Guided Reinforcement Learning for Black-Box LLM Jailbreaking
Sung-Hoon Yoon, Ruizhi Qian, Minda Zhao +2
Large Language Models (LLMs) have become integral to many domains, making their safety a critical priority. Prior jailbreaking research has explored diverse approaches, including p…
LLM Review: Enhancing Creative Writing via Blind Peer Review Feedback
Weiyue Li, Mingxiao Song, Zhenda Shen +6
Large Language Models (LLMs) often struggle with creative generation, and multi-agent frameworks that improve reasoning through interaction can paradoxically hinder creativity by i…
Grading Scale Impact on LLM-as-a-Judge: Human-LLM Alignment Is Highest on 0-5 Grading Scale
Weiyue Li, Minda Zhao, Weixuan Dong +12
Large language models (LLMs) are increasingly used as automated evaluators, yet prior works demonstrate that these LLM judges often lack consistency in scoring when the prompt is a…