Intelligent systems · Human ambition
Advanced · Analytical · Adaptive · Adventurous · Aspiring
arXiv preprint
EMNLP 2026 Main Conference
ICML 2026
arXiv preprint
EMNLP 2026 Findings
02 / Research areas
Theme 01
Lead · Ye Yuan
Diffusion, flow, and diffusion language models for design search on a static dataset, including calibrated estimation, support-proximity regularization, multi-objective guided flows, and settings where labels or experiments are expensive.
Theme 02
Lead · Bowei He
Benchmarks, training methods, and runtime frameworks for language agents that retrieve evidence, use tools, and learn from process-level rewards, including search-integrated reasoning, branching policy optimization, and scaling from one device to collective systems.
Theme 03
Lead · Haolun Wu
Aligning single models and compound AI systems with human preferences, including system-level direct preference optimization, logit-only adaptation of closed models, internal-representation safeguards, and human-centered control of model behavior.
Theme 04
Lead · Haolun Wu
Representing evolving user interests and keeping retrieved content scrutable, including density-based user modeling, retrieval-augmented personalization, interpretable preference heads, and diversification in search and recommendation.
Theme 05
Lead · Bowei He
Language models as rankers and sequential recommenders, grounded in entities, tables, and retrieved documents. This includes mutual augmentation between recommenders and LLMs, context-aware contrastive learning, embedding-based reranking, agentic table summarization, and retrieval-augmented generation.
Theme 06
Lead · Ye Yuan
Vision-language models and generative systems that read and produce across text, images, documents, and other discrete modalities, including multimodal retrieval, grounded multimodal agents, and diffusion models that move from tokenization through generation.
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