Bryan Hooi
- Papers
- 36
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Authored papers
36MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome
arXiv 2026
Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs
arXiv 2026
Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning
arXiv 2026
Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies
arXiv 2026
Safety in Large Reasoning Models: A Survey
arXiv 2025
MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research
arXiv 2025
FlowReasoner: Reinforcing Query-Level Meta-Agents
arXiv 2025
ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark
arXiv 2025
Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models
arXiv 2025
GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning
arXiv 2025
GuardReasoner: Towards Reasoning-based LLM Safeguards
arXiv 2025
Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
arXiv 2025
JudgeLRM: Large Reasoning Models as a Judge
arXiv 2025
Words or Vision: Do Vision-Language Models Have Blind Faith in Text?
CVPR 2025 1
Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
arXiv 2025
How Does Response Length Affect Long-Form Factuality
arXiv 2025
Automating Steering for Safe Multimodal Large Language Models
arXiv 2025
Efficient Inference for Large Reasoning Models: A Survey
arXiv 2025
Navigating the Helpfulness-Truthfulness Trade-Off with Uncertainty-Aware Instruction Fine-Tuning
arXiv 2025
Do "New Snow Tablets" Contain Snow? Large Language Models Over-Rely on Names to Identify Ingredients of Chinese Drugs
arXiv 2025
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
arXiv 2024
FlipAttack: Jailbreak LLMs via Flipping
arXiv 2024
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection
arXiv 2024
Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning
arXiv 2024
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding
arXiv 2024
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
arXiv 2023
Efficient Heterogeneous Graph Learning via Random Projection
arXiv 2023
Multimodal Graph Learning for Generative Tasks
arXiv 2023
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
arXiv 2023
Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View
arXiv 2023
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
arXiv 2023
A Generalization of ViT/MLP-Mixer to Graphs
arXiv 2022
Expanding Small-Scale Datasets with Guided Imagination
expanding-small-scale-datasets-with-guided
Deep Long-Tailed Learning: A Survey
arXiv 2021
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition
arXiv 2021
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning
NeurIPS 2021 12
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