Academic
arXiv:2602.20557v1 Announce Type: new Abstract: Symbolic Regression (SR) tries to reveal the hidden equations behind observed data. However, most methods search within a discrete equation …
arXiv:2602.20567v1 Announce Type: new Abstract: Push-Sum-based decentralized learning enables optimization over directed communication networks, where information exchange may be asymmetric. While convergence properties of such …
arXiv:2602.20573v1 Announce Type: new Abstract: Molecules are commonly represented as SMILES strings, which can be readily converted to fixed-size molecular fingerprints. These fingerprints serve as …
arXiv:2602.20578v1 Announce Type: new Abstract: We study online maximization of non-monotone Diminishing-Return(DR)-submodular functions over down-closed convex sets, a regime where existing projection-free online methods suffer …
arXiv:2602.19049v1 Announce Type: new Abstract: Large language models increasingly rely on long chains of thought to improve accuracy, yet such gains come with substantial inference-time …
arXiv:2602.19058v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have rapidly advanced across various domains, yet they still lag behind strong text-only large language models …
arXiv:2602.19079v1 Announce Type: new Abstract: Topic modeling extracts latent themes from large text collections, but leading approaches like BERTopic face critical limitations: stochastic instability, loss …
arXiv:2602.19101v1 Announce Type: new Abstract: Value alignment of Large Language Models (LLMs) requires us to empirically measure these models' actual, acquired representation of value. Among …
arXiv:2602.19111v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) methods, especially LoRA, are widely used for adapting pre-trained models to downstream tasks due to their computational …
arXiv:2602.19115v1 Announce Type: new Abstract: In recent years, there has been a growing use of generative AI, and large language models (LLMs) in particular, to …
arXiv:2602.19127v1 Announce Type: new Abstract: With the rapid advancement of agent-based methods in recent years, Agentic RAG has undoubtedly become an important research direction. Multi-hop …
