Home Knowledge Base Stage II

Stage II

No mentions found

This entity hasn't been tracked yet, or Iris is still building its knowledge base.

Related Articles from SNS

Detection of Pancreatic Cancer Using a Methylation-Specific PCR-Based Multi-Cancer Early Detection Test

Context: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy often diagnosed at advanced stages due to the lack of early clinical symptoms. DNA methylation alterations arise early in PDAC tumorigenesis and may serve as promising biomarkers for blood-based cancer detection. Objective: To evaluate the performance of EPISEEK, a laboratory-developed blood-based multi-cancer early detection (MCED) assay, for detecting PDAC across disease stages.

bioRxiv 11d ago

Scientists were excited about a blood test for many cancers — but it failed a big trial. Here's what to know.

Scientists were excited about a blood test for many cancers — but it failed a big trial. Emerging tests promise to screen for many cancers at once, but one just failed in a big trial. Will these diagnostics deliver on their promise someday?

Live Science 8h ago

FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models

arXiv:2606.06547v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) refine tokens iteratively but commit them irreversibly, leading to a "stability lag" where early decisions remain fragile even after being written. We reveal that Post-Training Quantization (PTQ) error easily flips these borderline decisions at the write frontier, which are then permanently locked in and amplified. To address this, we propose Frontier-Aware Instability-Reweighted Calibration (FAIR-Calib),...

arXiv CS 3d ago

To Grok Grokking: Provable Grokking in Ridge Regression

arXiv:2601.19791v3 Announce Type: replace Abstract: We study grokking, the onset of generalization long after overfitting, in a classical ridge regression setting. We prove end-to-end grokking results for learning over-parameterized linear regression models using gradient descent with weight decay. Specifically, we prove that the following stages occur: (i) the model overfits the training data early during training; (ii) poor generalization persists long after overfitting has manifested; and...

arXiv CS 10d ago

When drug discovery fails: scientists share their frustrations with the process

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer).

Nature 1d ago

Deep Research as Rubric for Reinforcement Learning

Announce Type: new Abstract: Open-ended reasoning and long-form generation tasks lack reliable automatic verification signals for reward-based policy optimization. Rubrics offer a promising alternative, but existing approaches treat them as given artifacts -- either hand-crafted or prompt-generated -- and often miss the task-specific, knowledge-intensive dimensions that matter most, distorting the reward signal. Our key observation is that rubric construction is itself a research problem:...

arXiv CS 9d ago

OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents

arXiv:2605.08876v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents that execute tool-augmented, multi-step tasks, where latency is a critical factor for real-world applications. Yet an overlooked threat is Reasoning-Level Denial-of-Service (R-DoS), in which an attacker preserves task correctness but degrades availability by inflating an agent's reasoning depth or tool-use budget.

arXiv CS 2d ago

TamperBench: Systematically Stress-Testing LLM Safety Under Fine-Tuning and Tampering

Announce Type: replace Abstract: As increasingly capable open-weight large language models (LLMs) are deployed, improving their tamper resistance against unsafe modifications, whether accidental or intentional, becomes critical to minimize risks. However, there is no standard approach to evaluate tamper resistance.

arXiv CS 7d ago

WebSpline: Structure-Informed Splines for Real-Time 3D Gaussians from Monocular Videos

arXiv:2606.02096v1 Announce Type: new Abstract: Dynamic scene reconstruction from monocular videos remains highly challenging, as existing methods often struggle to balance global structural coherence and local fine-grained details under limited multi-view cues. To address this challenge, we propose WebSpline, a novel dynamic 3D Gaussian framework that enables structurally coherent and high-fidelity reconstruction from monocular videos with fast rendering. The core of WebSpline is the...

arXiv CS 9d ago

$M^3$ Scaling Law: Optimizing Multi-Epoch, Multi-Lingual, and Multi-Stage Training for Low-Resource Language Models

arXiv:2410.12325v2 Announce Type: replace Abstract: In this paper, we study a fundamental design problem in pretraining Large Language Models (LLMs) for low-resource language regimes. Existing works adopt multi-epoch, multi-lingual, and multi-stage training to utilize the limited target-language corpus efficiently, but no prior scaling law can compare recipes spanning these approaches under the same compute budget $C$ and target-language corpus size $D_T$, leaving the optimal training setup...

arXiv CS 9d ago