Ward: Education

220

Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows

arXiv:2512.16969v1 Announce Type: new
Abstract: Despite advances in scientific AI, a coherent framework for Scientific General Intelligence (SGI)-the ability to autonomously conceive, investigate, and reason across scientific domains-remains lacking. We present an operational SGI definition grounde…

221

The Ten Most Significant Science Stories of 2025

Kranking, Prillaman, & Hill, Sonian Every December, Smithsonian magazine's science team picks which stories were the year's most significant. We look for a broad set of topics that...

109

Extended formulations for induced tree and path polytopes of chordal graphs

arXiv:2512.08554v2 Announce Type: replace
Abstract: In this article, we give two extended space formulations, respectively, for the induced tree and path polytopes of chordal graphs with vertex and edge variables.
These formulations are obtained by proving that the induced tree and path extended …

111

Explorable Ideas: Externalizing Ideas as Explorable Environments

arXiv:2512.17017v1 Announce Type: new
Abstract: Working with abstract information often relies on static, symbolic representations that constrain exploration. We introduce Explorable Ideas, a framework that externalizes abstract concepts into explorable environments where physical navigation coordi…

109

Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning

arXiv:2510.16882v2 Announce Type: replace
Abstract: Supervised fine-tuning (SFT) is a commonly used technique to adapt large language models (LLMs) to downstream tasks. In practice, SFT on a full dataset is computationally expensive and sometimes suffers from overfitting or bias amplification. This…

220

Refinement-based Christoffel sampling for least squares approximation in non-orthogonal bases

arXiv:2510.08461v2 Announce Type: replace
Abstract: We introduce a refinement-based Christoffel sampling (RCS) algorithm for least squares approximation in the span of a given, generally non-orthogonal set of functions $\Phi_n = \{\phi_1, \dots, \phi_n\}$. A standard sampling strategy for this prob…

234

Strategic Planning and Rationalizing on Trees Make LLMs Better Debaters

arXiv:2505.14886v2 Announce Type: replace
Abstract: Winning competitive debates requires sophisticated reasoning and argument skills. There are unique challenges in the competitive debate: (1) The time constraints force debaters to make strategic choices about which points to pursue rather than cov…

109

Alzheimer's Disease Brain Network Mining

arXiv:2512.17276v1 Announce Type: new
Abstract: Machine learning approaches for Alzheimer's disease (AD) diagnosis face a fundamental challenges. Clinical assessments are expensive and invasive, leaving ground truth labels available for only a fraction of neuroimaging datasets. We introduce Multi v…

423

Ancient sea anemone sheds light on animal cell type evolution

One of the biggest quests in biology is understanding how every cell in an animal's body carries an identical genome yet still gives rise to a kaleidoscope of different cell types and tissues. A neuron doesn't look nor behave like a muscle cell but has the same DNA.

111

Robust-R1: Degradation-Aware Reasoning for Robust Visual Understanding

arXiv:2512.17532v1 Announce Type: new
Abstract: Multimodal Large Language Models struggle to maintain reliable performance under extreme real-world visual degradations, which impede their practical robustness. Existing robust MLLMs predominantly rely on implicit training/adaptation that focuses sol…

210

Deterministic implementation in single-item auctions

arXiv:2512.17386v1 Announce Type: new
Abstract: Deterministic auctions are attractive in practice due to their transparency, simplicity, and ease of implementation, motivating a sharp understanding of when they match randomized designs. We study deterministic implementation in single-item auctions …

120

More Consistent Accuracy PINN via Alternating Easy-Hard Training

arXiv:2512.17607v1 Announce Type: new
Abstract: Physics-informed neural networks (PINNs) have recently emerged as a prominent paradigm for solving partial differential equations (PDEs), yet their training strategies remain underexplored. While hard prioritization methods inspired by finite element …

212

Hubble Captures the Dramatic Aftermath of Colliding Space Rocks

Northwestern In an unprecedented celestial event, NASA's Hubble Space Telescope (HST) captured the dramatic aftermath of colliding space rocks within a nearby planetary system.
When...

212

Optimal Error Analysis of Channel Estimation for IRS-assisted MIMO Systems

arXiv:2412.16827v2 Announce Type: replace
Abstract: As intelligent reflecting surface (IRS) has emerged as a new and promising technology capable of configuring the wireless environment favorably, channel estimation for IRS-assisted multiple-input multiple-output (MIMO) systems has garnered extensi…

122

STAT+: A seasoned biotech VC looks to 2026 and sees a wave of IPOs coming

One of the biotech industry’s most esteemed venture capitalists anticipates that, after two years of drought, a wave of drug companies are set to go public.

222

A top global design alliance is embracing AI to ‘let designers focus more on empathy and creativity’

Many designers are increasingly warming to the idea of incorporating AI in design, says Cecilia Brenner, the managing director of Design for Good, a global design charity.

318

Software Sheds Light on Cancer's Hidden Networks

Universidad de Navarra Researchers at the University of Navarra have developed RNACOREX, open-source software capable of identifying Genetics regulatory networks Genetics applications in...

212

New Hybrid Heuristics for Pseudo-Boolean Propagation

arXiv:2511.21417v2 Announce Type: replace
Abstract: In pseudo-boolean solving the currently most successful unit propagation strategy is a hybrid mode combining the watched literal scheme with the counting method. This short paper introduces new heuristics for this hybrid decision, which are able t…

109

Refining the Complexity Landscape of Speed Scaling: Hardness and Algorithms

arXiv:2512.17663v1 Announce Type: new
Abstract: We study the computational complexity of scheduling jobs on a single speed-scalable processor with the objective of capturing the trade-off between the (weighted) flow time and the energy consumption. This trade-off has been extensively explored in th…

219

Taming the Memory Footprint Crisis: System Design for Production Diffusion LLM Serving

arXiv:2512.17077v1 Announce Type: new
Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to Autoregressive Models (ARMs), utilizing parallel decoding to overcome sequential bottlenecks. However, existing research focuses primarily on kernel-level optimizations…