From the 1 of 40 linked papers with an AI index.
1 citations · 1 across the 14 of their papers we have counts for
5 papers · 1 filter
When Do Multi-Agent Systems Help? An Information Bottleneck Perspective
Wendi Yu, Lianhao Zhou, Xiangjue Dong +6
LLM powered multi-agent systems (MAS) have emerged as a promising paradigm for complex tasks. However, their advantages over single-agent systems (SAS) remain unclear, with perform…
Visual Species Recognition with Large Multimodal Models as Post-Hoc Correctors
Tian Liu, Anwesha Basu, James Caverlee +1
The paper introduces a training-free post-hoc correction framework that uses large multimodal models to improve few-shot expert models for visual species recognition, boosting accu…
Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
Shubham Parashar, Shurui Gui, Xiner Li +8
We aim to improve the reasoning capabilities of language models via reinforcement learning (RL). Recent RL post-trained models like DeepSeek-R1 have demonstrated reasoning abilitie…
BI-DCGAN: A Theoretically Grounded Bayesian Framework for Efficient and Diverse GANs
Mahsa Valizadeh, Rui Tuo, James Caverlee
Generative Adversarial Networks (GANs) are proficient at generating synthetic data but continue to suffer from mode collapse, where the generator produces a narrow range of outputs…
Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation
Haoran Liu, Youzhi Luo, Tianxiao Li +2
We consider the conditional generation of 3D drug-like molecules with \textit{explicit control} over molecular properties such as drug-like properties (e.g., Quantitative Estimate…