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Hanlin Wu

7 accepted papers

2026

A Synthetic Benchmark for Collaborative 3D Semantic Occupancy Prediction in V2X-Enabled Autonomous Driving

ICRA 2026poster

3D semantic occupancy prediction is an emerging perception paradigm in autonomous driving, providing a voxel-level representation of both geometric details and semantic categories. However, despite its fine-grained scene understanding, its effectiveness is inherently constrained in single-vehicle se…

2026

Beyond Euclidean Clipping: Overcoming Exploration Collapse in LLM RL via Riemannian Isometric Policy Optimization

ICML 2026poster

Reinforcement learning (RL) has become a dominant paradigm for enhancing LLMs' reasoning capabilities. However, RL algorithms with PPO-Clip are inherently limited by exploration collapse. Subsequent works remain primarily heuristic and fail to identify the essential cause of PPO-Clip’s failure. This…

Cited by 0SourceScholar
2025

A Periodic Bayesian Flow for Material Generation

ICLR 2025spotlight

Generative modeling of crystal data distribution is an important yet challenging task due to the unique periodic physical symmetry of crystals. Diffusion-based methods have shown early promise in modeling crystal distribution. More recently, Bayesian Flow Networks were introduced to aggregate noisy…

2025

Accelerating 3D Molecule Generative Models with Trajectory Diagnosis

NeurIPS 2025poster

Geometric molecule generative models have found expanding applications across various scientific domains, but their generation inefficiency has become a critical bottleneck. Through a systematic investigation of the generative trajectory, we discover a unique challenge for molecule geometric graph g…

Cited by 0SourceScholar
2025

ChangeChat: An Interactive Model for Remote Sensing Change Analysis via Multimodal Instruction Tuning

ICASSP 2025accepted

Remote sensing (RS) change analysis is vital for monitoring Earth’s dynamic processes by detecting alterations in images over time. Traditional change detection methods excels at identifying pixel-level changes but lacks the ability to contextualize these changes. While recent advancements in change…

Cited by 0SourceScholar
2025

MOF-BFN: Metal-Organic Frameworks Structure Prediction via Bayesian Flow Networks

NeurIPS 2025poster

Metal-Organic Frameworks (MOFs) have attracted considerable attention due to their unique properties including high surface area and tunable porosity, and promising applications in catalysis, gas storage, and drug delivery. Structure prediction for MOFs is a challenging task, as these frameworks are…

Cited by 0SourceScholar
2025

Rationalized All-Atom Protein Design with Unified Multi-Modal Bayesian Flow

NeurIPS 2025poster

Designing functional proteins is a critical yet challenging problem due to the intricate interplay between backbone structures, sequences, and side-chains. Current approaches often decompose protein design into separate tasks, which can lead to accumulated errors, while recent efforts increasingly f…

Cited by 0SourceScholar