YouZum

News

News

Open World Knowledge Aided Single-Cell Foundation Model with Robust Cross-Modal Cell-Language Pre-training

arXiv:2601.05648v1 Announce Type: cross Abstract: Recent advancements in single-cell multi-omics, particularly RNA-seq, have provided profound...

ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models

arXiv:2507.00898v1 Announce Type: cross Abstract: Recent Large Vision-Language Models (LVLMs) have introduced a new paradigm...

Online-PVLM: Advancing Personalized VLMs with Online Concept Learning

arXiv:2511.20056v1 Announce Type: new Abstract: Personalized Visual Language Models (VLMs) are gaining increasing attention for...

Online harassment is entering its AI era

Scott Shambaugh didn’t think twice when he denied an AI agent’s request to contribute to...

One-Token Rollout: Guiding Supervised Fine-Tuning of LLMs with Policy Gradient

arXiv:2509.26313v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is the predominant method for adapting large...

One Trigger Token Is Enough: A Defense Strategy for Balancing Safety and Usability in Large Language Models

arXiv:2505.07167v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have been extensively used across diverse...

One Token Is Enough: Improving Diffusion Language Models with a Sink Token

arXiv:2601.19657v3 Announce Type: replace Abstract: Diffusion Language Models (DLMs) have emerged as a compelling alternative...

One Joke to Rule them All? On the (Im)possibility of Generalizing Humor

arXiv:2508.19402v1 Announce Type: new Abstract: Humor is a broad and complex form of communication that...

On the Reliability of Large Language Models for Causal Discovery

arXiv:2407.19638v2 Announce Type: replace Abstract: This study investigates the efficacy of Large Language Models (LLMs)...

On the generalization of language models from in-context learning and finetuning: a controlled study

arXiv:2505.00661v2 Announce Type: replace Abstract: Large language models exhibit exciting capabilities, yet can show surprisingly...

On the Effectiveness of Membership Inference in Targeted Data Extraction from Large Language Models

arXiv:2512.13352v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are prone to memorizing training data...

We use cookies to improve your experience and performance on our website. You can learn more at Privacy Policy and manage your privacy settings by clicking Settings.

Privacy Preferences

You can choose your cookie settings by turning on/off each type of cookie as you wish, except for essential cookies.

Allow All
Manage Consent Preferences
  • Always Active

Save
en_US