PPaperPicks

Xiaotian Han

23 papers at tracked venues · 17 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization
  2. InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning and Reflection
  3. Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers
  4. Quantize What Counts: More for Keys, Less for Values
  5. 100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability?
  6. All You Need is One: Capsule Prompt Tuning with a Single Vector
  7. CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation
  8. Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks
  9. InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning
    EMNLP 2025 · Xiaotian Han
  10. Longer Context, Deeper Thinking: Uncovering the Role of Long-Context Ability in Reasoning
  11. MEPT: Mixture of Expert Prompt Tuning as a Manifold Mapper
  12. NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models
  13. Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs
  14. Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs
  15. When Truthful Representations Flip Under Deceptive Instructions?
  16. Chasing Fairness in Graphs: A GNN Architecture Perspective
  17. DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation
  18. FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
    ICLR 2024 · Xiaotian Han
  19. Gradient Rewiring for Editable Graph Neural Network Training
  20. InfiMM: Advancing Multimodal Understanding with an Open-Sourced Visual Language Model
  21. LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning
  22. PokeMQA: Programmable knowledge editing for Multi-hop Question Answering
  23. Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model