Ward: Education

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…

119

Biosecurity-Aware AI: Agentic Risk Auditing of Soft Prompt Attacks on ESM-Based Variant Predictors

arXiv:2512.17146v1 Announce Type: new
Abstract: Genomic Foundation Models (GFMs), such as Evolutionary Scale Modeling (ESM), have demonstrated remarkable success in variant effect prediction. However, their security and robustness under adversarial manipulation remain largely unexplored. To address…

109

Computational analysis reveals historical trajectory of East-Polynesian lunar calendars

arXiv:2512.17525v1 Announce Type: cross
Abstract: We investigate a type of lunar calendar known as lists of the 'nights of the moon', found throughout East Polynesia, including Rapa Nui (Easter Island). Using computational methods, we analyzed the lexical and structural divergence of 49 calendric l…

332

Derivates for Containers in Univalent Foundations

arXiv:2512.17484v1 Announce Type: new
Abstract: Containers conveniently represent a wide class of inductive data types. Their derivatives compute representations of types of one-hole contexts, useful for implementing tree-traversal algorithms. In the category of containers and cartesian morphisms, …

122

Linear Attention for Joint Power Optimization and User-Centric Clustering in Cell-Free Networks

arXiv:2512.17466v1 Announce Type: new
Abstract: Optimal AP clustering and power allocation are critical in user-centric cell-free massive MIMO systems. Existing deep learning models lack flexibility to handle dynamic network configurations. Furthermore, many approaches overlook pilot contamination …

112

Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference

arXiv:2509.21791v3 Announce Type: replace
Abstract: Structured output from large language models (LLMs) has enhanced efficiency in processing generated information and is increasingly adopted in industrial applications. Prior studies have investigated the impact of structured output on LLMs' genera…

111

When Safety Blocks Sense: Measuring Semantic Confusion in LLM Refusals

arXiv:2512.01037v2 Announce Type: replace
Abstract: Safety-aligned language models often refuse prompts that are actually harmless. Current evaluations mostly report global rates such as false rejection or compliance. These scores treat each prompt alone and miss local inconsistency, where a model …

221

PhysGM: Large Physical Gaussian Model for Feed-Forward 4D Synthesis

arXiv:2508.13911v2 Announce Type: replace
Abstract: Despite advances in physics-based 3D motion synthesis, current methods face key limitations: reliance on pre-reconstructed 3D Gaussian Splatting (3DGS) built from dense multi-view images with time-consuming per-scene optimization; physics integrat…

321

Computing measures of weak-MSO definable sets of trees

arXiv:2410.13479v2 Announce Type: replace
Abstract: This work addresses the problem of computing measures of recognisable sets of infinite trees. An algorithm is provided to compute the probability measure of a tree language recognisable by a weak alternating automaton, or equivalently definable in…

109

VAIR: Visual Analytics for Injury Risk Exploration in Sports

arXiv:2512.17446v1 Announce Type: new
Abstract: Injury prevention in sports requires understanding how bio-mechanical risks emerge from movement patterns captured in real-world scenarios. However, identifying and interpreting injury prone events from raw video remains difficult and time-consuming. …

323

One Protein Is a Better Predictor of Heart Disease Than Cholesterol

It's always more complicated.

109

Ancient DNA Reveals Surprising Truth of Beachy Head Woman's Identity

She's not who we thought.

111

Planning as Descent: Goal-Conditioned Latent Trajectory Synthesis in Learned Energy Landscapes

arXiv:2512.17846v1 Announce Type: new
Abstract: We present Planning as Descent (PaD), a framework for offline goal-conditioned reinforcement learning that grounds trajectory synthesis in verification. Instead of learning a policy or explicit planner, PaD learns a goal-conditioned energy function ov…

211

Bridging Training and Merging Through Momentum-Aware Optimization

arXiv:2512.17109v1 Announce Type: new
Abstract: Training large neural networks and merging task-specific models both exploit low-rank structure and require parameter importance estimation, yet these challenges have been pursued in isolation. Current workflows compute curvature information during tr…