SGNTUCollege of Computing and Data Science
Dacheng TaoDistinguished University Professor
Applies statistics and mathematics to artificial intelligence, including computer vision, deep learning theory and large models.
- Learning theory & optimization
- Data management & big data
- Large language models
- 2026A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning ModelsICLR
- 2026AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward OptimizationAAAI
346 T1 · 501 papers · Group size not listed SGNUSDepartment of Computer Science
Works on multimodal foundation models, conversational search and recommendation, and trust and safety of AI; co-directs the NExT search centre.
- Large language models
- Interpretability, evaluation & safety of LMs
- Recommendation, search & web
- 2026ADVersa: Abductive Driving Accident Video UnderstandingTPAMI
- 2026AlphaSteer: Learning Refusal Steering with Principled Null-Space ConstraintICLR
215 T1 · 319 papers · Group size not listed · 37 alumni USUT AustinElectrical and Computer Engineering
Leads the VITA Group, working on efficient and robust deep learning, sparse neural networks and large language models.
- Trustworthy & safe ML
- Large language models
- Efficient training & inference
- 2026A Physics-Grounded Benchmark for Multi-Agent Dynamics in World ModelsECCV
- 2026Beyond Test-Time Memory: State-Space Optimal Control for LLM ReasoningICML
165 T1 · 197 papers · 15 members · 45 alumni CNTsinghuaDepartment of Computer Science and Technology
Works on large language models, knowledge graphs and semantic computing, and computational social science.
- Large language models
- Knowledge, QA & retrieval
- Graph mining & networks
- 2026APB-V: Accelerating Long-Video Understanding via Sequence-Parallelism-aware Approximate AttentionACL
- 2026AutoReproduce: Automatic AI Experiment Reproduction with Paper LineageACL
133 T1 · 203 papers · 24 members · 27 alumni CNTsinghuaDepartment of Computer Science and Technology
Works on natural language processing, large models, Chinese information processing, and computing for the humanities and arts.
- 2026A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent TaskACL
- 2026AutoReproduce: Automatic AI Experiment Reproduction with Paper LineageACL
122 T1 · 190 papers · 48 members · 123 alumni CNSJTUSchool of Artificial Intelligence
Works on AI for media and healthcare, including medical foundation models.
- Medical imaging & healthcare AI
- Generative & foundation models
- Large language models
- 2026Cross-Modal Coreference Alignment: Enabling Reliable Information Transfer in Omni-LLMsACL
- 2026GenMask: Adapting DiT for Segmentation via Direct Mask GenerationCVPR
119 T1 · 180 papers · Group size not listed CNZhejiangSchool of Artificial Intelligence
Kun KuangAssociate Professor
Studies causal inference and its integration with machine learning, including causal AI for smart justice and domain-specific large models.
- Probabilistic & causal inference
- Efficient training & inference
- Large language models
- 2026"I Don’t Know What to Say": A Fact-Filling Questionnaire Method to Help Non-Experts Talk to LegalAI AssistantACL
- 2026Asynchronous Denoising Diffusion Models for Aligning Text-to-Image GenerationICLR
115 T1 · 143 papers · Group size not listed USUIUCSiebel School of Computing and Data Science
Studies natural language processing, including information extraction, knowledge-enhanced language models and multimedia multilingual understanding.
- Knowledge, QA & retrieval
- Large language models
- Data management & big data
- 2026Advancing Creative Physical Intelligence in Large Multimodal ModelsNeurIPS
- 2026Agentic Reasoning for Large Language Models: A SurveyTMLR
114 T1 · 258 papers · 17 members · 135 alumni SGNUSDepartment of Computer Science
Builds data systems and infrastructure for large language models and agentic AI, federated learning and graph analytics on GPUs, TPUs and FPGAs.
- Accelerators, chips & architecture
- Distributed, cloud & edge systems
- Large language models
- 2026'They've Stolen My GPL-Licensed Model!': Toward Standardized and Transparent Model LicensingWWW
- 2026ABFlow: Alert Bursting Flow Query in Streaming Temporal Flow NetworksSIGMOD
110 T1 · 134 papers · 7 members · 12 alumni CNZhejiangCollege of Computer Science and Technology
Researches computer vision and machine learning, including dense prediction, detection and segmentation, and vision foundation models.
- Recognition, detection & segmentation
- Generative & foundation models
- Large language models
- 2026\(\pi^3\): permutation-equivariant visual geometry learningICLR
- 2026ACTIVE-O3: empowering multimodal large language models with active perception via GRPOICML
109 T1 · 116 papers · 15 members · 12 alumni USUCLAComputer Science
Develops natural language processing and machine learning methods, including vision-language models, robustness and fairness of language models.
- Large language models
- Interpretability, evaluation & safety of LMs
- Vision-language & multimodal
- 2026ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward SystemACL
- 2026ContextNav: Towards Agentic Multimodal In-Context LearningICLR
104 T1 · 152 papers · 12 members · 46 alumni USStanfordComputer Science
Yejin ChoiDieter Schwarz Foundation Professor of Computer Science, Senior Fellow at the Stanford Institute for Human-Centered AI
Studies large language models, commonsense reasoning and the limits of language model generalization.
- Large language models
- Reasoning & agents
- Learning theory & optimization
- 2026Activation Steering for LLM Alignment via a Unified ODE-Based FrameworkICLR
- 2026BroRL: Scaling Reinforcement Learning via Broadened ExplorationICML
102 T1 · 170 papers · 7 members · 63 alumni GBImperialDepartment of Computing
Jiankang DengAssistant Professor in Computing
Directs the MVP Lab on multi-modal foundation models for visual, acoustic and tactile signals and generative modelling of the physical world.
- Vision-language & multimodal
- Generative & foundation models
- Large language models
- 2026Beyond Description: Cognitively Benchmarking Fine-Grained Action for Embodied AgentsECCV
- 2026CASteer: Cross-Attention Steering for Controllable Concept ErasureICLR
97 T1 · 107 papers · 6 members · 4 alumni USUIUCSiebel School of Computing and Data Science
Studies data mining and text mining, including knowledge graph construction, information network analysis and mining with large language models.
- Graph mining & networks
- Data management & big data
- Large language models
- 2026Condition-Gated Reasoning for Context-Dependent Biomedical Question AnsweringKDD
- 2026CoRank: LLM-Based Compact Reranking with Document Features for Scientific RetrievalKDD
95 T1 · 127 papers · 14 members · 151 alumni USUIUCSiebel School of Computing and Data Science
Studies machine learning theory and algorithms, including optimization, reinforcement learning and alignment of large language models.
- Learning theory & optimization
- Reinforcement learning
- Large language models
- 2026"A Sharp KL-Convergence Analysis for Diffusion Models under Minimal AssumptionsICLR
- 2026"Almost linear convergence under minimal score assumptions: Quantized transition diffusionCOLT
89 T1 · 104 papers · 13 members · 36 alumni USUCLAComputer Science
Researches controllable and creative language generation, multimodal language models and evaluation of language model reasoning.
- Large language models
- Reasoning & agents
- Vision-language & multimodal
- 2026ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy ShapingICLR
- 2026Decoupling Task-Solving and Output Formatting in LLM GenerationACL
87 T1 · 136 papers · 9 members · 35 alumni SGNTUCollege of Computing and Data Science
Works on natural language processing, including LLM reasoning, multilingual and multimodal language models, discourse and question answering.
- Large language models
- Reasoning & agents
- Vision-language & multimodal
- 2026Can Vibe Coders Really Pass the Vibe Check? An Empirical Analysis of Fault-Targeted Reasoning in Frontier LLMsEMNLP
- 2026Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token ReductionACL
85 T1 · 110 papers · 1 member · 16 alumni USCMULanguage Technologies Institute
Studies language models and AI agents, including code generation, multilingual NLP and evaluation.
- Large language models
- Reasoning & agents
- 2026Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM AgentsICLR
- 2026Ambig-SWE: Interactive Agents to Overcome Underspecificity in Software EngineeringICLR
81 T1 · 124 papers · 15 members · 37 alumni USUCLAComputer Science
Develops nonconvex optimization and learning theory, and alignment and reasoning methods for large language models.
- Learning theory & optimization
- Trustworthy & safe ML
- Large language models
- 2026Best-of-Majority: Minimax-Optimal Strategy for Pass@k Inference ScalingICLR
- 2026Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action SetICLR
73 T1 · 91 papers · 9 members · 60 alumni USUWPaul G. Allen School of Computer Science & Engineering
Researches large language models, semantic parsing and multimodal pretraining.
- Large language models
- Multilingual, translation & linguistics
- Vision-language & multimodal
- 2026High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned FinetuningICLR
- 2026Latent Speech-Text TransformerICLR
72 T1 · 87 papers · 11 members · 34 alumni