Reforming the Mechanism: Editing Reasoning Patterns in LLMs with Circuit Reshaping

REdit reshapes LLM neural circuits before editing to reduce reasoning-pattern interference, improving generality and locality over broad training baselines.

Zhenyu Lei, Qiong Wu, Jianxiong Dong, Yinhan He and 3 more

Published Jan 25, 2026 · 0 citations

BrainMAP: Learning Multiple Activation Pathways in Brain Networks

BrainMAP learns multiple brain network activation pathways via sequential models and Mixture-of-Experts, improving fMRI analysis and interpretability.

Song Wang, Zhenyu Lei, Zhen Tan, Jiaqi Ding and 7 more

Published Apr 11, 2025 · 2 citations

Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective

A spectral benchmark reveals that graph neural networks capture diverse frequency components through non-linear layers, not just neighborhood aggregation filters.

Yushun Dong, Patrick Soga, Yinhan He, Song Wang and 1 more

Published Dec 10, 2024 · 1 citation

LatentRouter: Can We Choose the Right Multimodal Model Before Seeing Its Answer?

Xueqi Cheng, Yushun Dong

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

GraphIP–Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?

Kaixiang Zhao, Bolin Shen, Yuyang Dai, Shayok Chakraborty and 1 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

PRO: Enabling Precise and Robust Text Watermark for Open-Source LLMs

Jiaqi Xue, Yifei Zhao, Mansour Al Ghanim, Shangqian Gao and 3 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

A Topological Encoder Decoder Framework for Temporal Graph Learning

Ronan Buck, Kiarash Shamsi, Tran Gia Bao Ngo, Astrit Tola and 2 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

Neural Expansion: A Unified Mechanism for How Deep Neural Network Generalize

Chashi Mahiul Islam, Samuel Jacob Chacko, Mao Nishino, Canlin Zhang and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

BEAST3D: animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting

BEAST3D relates 3D behavioral features from multi-view video to neural activity via Gaussian splatting. It establishes a versatile framework for behavioral analysis using 3D structure in laboratory recordings.

Yanchen Wang, Lenny Aharon, Wangshu Zhu, Kyle Daruwalla and 6 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Active Learning for Conditional Generative Compressed Sensing

For conditional generative compressed sensing, prompt-matched Christoffel sampling achieves near-optimal recovery bounds while prompt mismatch adds explicit penalties, with experiments showing prompts reshape sensing and recovery.

Alexander DeLise, Nick Dexter

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

E4GEN: Event-level Explainable Extreme-Enhanced Time-series Generation

E4GEN is an explainable diffusion framework that learns adaptive extreme-control signals for time-series generation, outperforming state-of-the-art models in overall fidelity, extreme-event fidelity, and downstream utility.

Lin Jiang, Dahai Yu, Ximiao Li, Guang Wang

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

Efficient Transferable Optimal Transport via Min-Sliced Transport Plans

Min-sliced transport plans transfer optimized slicers across related distributions with theoretical guarantees and efficient minibatch scaling for matching and generation.

Xinran Liu, Elaheh Akbari, Rocio Diaz Martin, Navid NaderiAlizadeh and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026