Jiaqing Xie

Cell-Lens: Advancing LLM Reasoning at Single-Cell Resolution

Equivariant Neural Primal-Dual Assignment for Maximum Common Edge Subgraphs

This work introduces Equivariant Neural Primal-Dual Assignment (ENPDA), which learns a shared matching policy and applies it to new pairs without further training, answering queries roughly three orders of magnitude faster and recovering its training cost after a few dozen queries.

Analytic-Walk Rotary Positional Encodings for Graphs

Analytic-Walk Rotary Positional Encodings (AW-RoPE), which place the rotations on edges and sum the transported features over all walks, so contributions along different routes can reinforce or cancel and prove forward and parameter-derivative truncation bounds at fixed inputs and parameters.

Disagree to Accelerate: Closing the Loop on Diffusion Feature Forecasts

This work introduces RACER, a training-free closed-loop controller that continuously shrinks uncertain forecasts toward the last computed feature and derives a deterministic error bound for the shrinkage and empirically evaluates its validity and tightness across acceleration regimes.

$\text{GSF-}\chi$: Global Stereochemical Fields for Chiral Graph Transformers

Enantiomers share atoms, bonds, and pairwise distances yet can behave differently in chiral environments, so molecular encoders must respect atom relabelings and proper rotations without becoming blind to reflection. We introduce GSF-$\chi$, a graph transformer in which stereogenic units modulate all pairwise interacti...

ABOPD: Antibody CDR Design via On-Policy Distillation

ABOPD is introduced, an antibody design framework based on on-policy distillation that leverages privileged native geometry during training to supervise states visited along the model's own denoising trajectories, offering a path to higher-fidelity protein design.

Reachability Is Not Realization: Tracing the Sources of LLM Benchmark Gains

This work establishes a question-level audit under fixed budgets, temperatures, and answer formats, and asks why reachable answers sometimes fail to appear, and test whether inference-time layer routing can expand reachability.