Yi Chang

Native Adaptive Solution Expansion for Diffusion-based Combinatorial Optimization

BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models

Decomposing Prompts: Discovering Reusable Scaffolds and Task-Specific Residuals

RD-HRL: Generating Reliable Sub-Goals for Long-Horizon Sparse-Reward Tasks

Distribution-Aware Multi-Granularity Phase Coding: Towards Lower Conversion Error for Spike-Driven Large Language Models

Three Forward, One Backward: Memory-Efficient Full-Rank Fine-Tuning of Large Models via Extra Forward Passes

Online Black-Box Prompt Optimization with Regret Guarantees under Noisy Feedback

THINK-Bench: Evaluating Thinking Efficiency and Chain-of-Thought Quality of Large Reasoning Models

Align, Don’t Divide: Revisiting the LoRA Architecture in Multi-Task Learning

MeTA-LoRA: Data-Efficient Multi-Task Fine-Tuning for Large Language Models

Achieve Latency-Efficient Tempora-Coding Spiking LLMs via Discretization-Aware Conversion

LLM as an Algorithmist: Enhancing Anomaly Detectors via Programmatic Synthesis

Imitating the Truth: Attention-aware Truth-Guided Enhancement for Hallucination Mitigation in Large Vision-Language Models

EvoCF: Multi-agent Collaboration with Memory-guided Evolutionary Counterfactual Planning

Training a Vision-Language Model for Diverse Exploration in Open GUI World

Beyond Accuracy: Measuring Reward Variance as a Predictive Benchmark for RLHF

Symmetry-Guaranteed Prediction of High-Order Tensor Properties for Crystalline Materials via Irreducible Decomposition

How to Get Spiking LLMs? A Dual ANN-to-SNN Conversion with Layer-Wise Calibration

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making

Mixup Model Merge: Enhancing Model Merging Performance through Randomized Linear Interpolation

ConfProBench: A Confidence Evaluation Benchmark for MLLM-based Process Judges

SegRet: An Efficient Design for Semantic Segmentation with Retentive Network

ProDA: Profile-Decomposed Adaptation for Capturing the Structured Residual in Low-Rank Updates

Explicit Column Relationship-Based Diffusion Model for High-Quality Synthetic Tabular Data Generation

Value Shaping: Bias Reduction in Bellman Error for Deep Reinforcement Learning

LLM Meeting Decision Trees on Tabular Data

Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning

InstructFlow: Adaptive Symbolic Constraint-Guided Code Generation for Long-Horizon Planning

StruDiCO: Structured Denoising Diffusion with Gradient-free Inference-stage Boosting for Memory and Time Efficient Combinatorial Optimization

Tackling Continual Offline RL through Selective Weights Activation on Aligned Spaces

FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning

Accelerated Vertical Federated Adversarial Learning through Decoupling Layer-Wise Dependencies

Collaborative Discrete-Continuous Black-Box Prompt Learning for Language Models

FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking

Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning

DRL: Decomposed Representation Learning for Tabular Anomaly Detection

Dual Variance Reduction with Momentum for Imbalanced Black-Box Discrete Prompt Learning

ContraDiff: Planning Towards High Return States via Contrastive Learning

BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models

Large Language Model Evaluation via Matrix Nuclear-Norm

Solving Continual Offline RL through Selective Weights Activation on Aligned Spaces

Rethinking Data Selection at Scale: Random Selection is Almost All You Need

Accelerate Vertical Federated Adversarial Learning with Dual-level Decoupled Backpropagation

Learning on Graphs with Large Language Models (LLMs): A Deep Dive into Model Robustness

Overcoming Missing Label Vocabulary in Black-Box Discrete Prompt Learning