Jianwen Sun
11 papers · 2020–2026 · 5 conferences · across top CS/AI conferences
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π Interdisciplinary Bridge π Conference Polyglot (4) π Academic Marathon (5) π Renaissance Researcher (8) πΊοΈ Taxonomy Completionist (35)
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Renaissance Researcher
(8)
π
Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(35)
π₯
Mega-Team
(21)
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Century Club
(10)
ποΈ
Keyword Collector
(61)
Conferences
AAAI (6)
EMNLP (2)
ACL (1)
ICCV (1)
NIPS (1)
Top co-authors
Keywords
large language model
(4)
reasoning evaluation
(2)
cognitive modeling
(2)
domain generalization
(2)
mathematical reasoning
(2)
multi-agent system
(2)
performance optimization
(1)
error detection
(1)
benchmark evaluation
(1)
synthetic data generation
(1)
preference optimization
(1)
resource allocation
(1)
adversarial attack
(1)
continuous action space
(1)
policy optimization
(1)
geometry reconstruction
(1)
human-ai collaboration
(1)
synthetic datum
(1)
3d gaussian splatting
(1)
adversarial perturbation
(1)
Papers
Invariant Representation Learning for Memory Behavior Modeling via Adaptive Environment Separation
AAAI 2026
MeepleLM: A Virtual Playtester Simulating Diverse Subjective Experiences
ACL 2026
MDK12-Bench: A Multi-Discipline Benchmark for Evaluating Reasoning in Multimodal Large Language Models
AAAI 2026
InMind: Evaluating LLMs in Capturing and Applying Individual Human Reasoning Styles
EMNLP 2025
VCR: A βCone of Experienceβ Driven Synthetic Data Generation Framework for Mathematical Reasoning
AAAI 2025
Empowering Math Problem Generation and Reasoning for Large Language Model via Synthetic Data based Continual Learning Framework
EMNLP 2025
ProJudge: A Multi-Modal Multi-Discipline Benchmark and Instruction-Tuning Dataset for MLLM-based Process Judges
ICCV 2025
Balancing Humans and Machines: A Study on Integration Scale and Its Impact on Collaborative Performance
AAAI 2024
Epipolar-Free 3D Gaussian Splatting for Generalizable Novel View Synthesis
NIPS 2024
Continuous Multiagent Control Using Collective Behavior Entropy for Large-Scale Home Energy Management
AAAI 2020
Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning
AAAI 2020