Cybersecurity’s Role in Securing Elections
SPEAKERS: Professor Chris Hoofnagle, Beth Calley, Lucy Huang Podcast Transcript: [Lucy Huang] 00:07 Hello and welcome to the Berkeley Technology Law Journal podcast. My name is Lucy Huang and I am one of the senior editors of the podcast. Today,...
FCC chair calls Paramount/WBD merger "a lot cleaner" than defunct Netflix deal
FCC to review foreign debt, but Carr indicates it will be a formality.
BRIDGE the Gap: Mitigating Bias Amplification in Automated Scoring of English Language Learners via Inter-group Data Augmentation
arXiv:2602.23580v1 Announce Type: new Abstract: In the field of educational assessment, automated scoring systems increasingly rely on deep learning and large language models (LLMs). However, these systems face significant risks of bias amplification, where model prediction gaps between student groups...
Benchmarking BERT-based Models for Sentence-level Topic Classification in Nepali Language
arXiv:2602.23940v1 Announce Type: new Abstract: Transformer-based models such as BERT have significantly advanced Natural Language Processing (NLP) across many languages. However, Nepali, a low-resource language written in Devanagari script, remains relatively underexplored. This study benchmarks multilingual, Indic, Hindi, and Nepali...
Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
arXiv:2602.24009v1 Announce Type: cross Abstract: Jailbreak techniques for large language models (LLMs) evolve faster than benchmarks, making robustness estimates stale and difficult to compare across papers due to drift in datasets, harnesses, and judging protocols. We introduce JAILBREAK FOUNDRY (JBF),...
FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments
arXiv:2602.23504v1 Announce Type: new Abstract: Federated Learning (FL) enables a group of clients to collaboratively train a model without sharing individual data, but its performance drops when client data are heterogeneous. Clustered FL tackles this by grouping similar clients. However,...
MPU: Towards Secure and Privacy-Preserving Knowledge Unlearning for Large Language Models
arXiv:2602.23798v1 Announce Type: new Abstract: Machine unlearning for large language models often faces a privacy dilemma in which strict constraints prohibit sharing either the server's parameters or the client's forget set. To address this dual non-disclosure constraint, we propose MPU,...
ULW-SleepNet: An Ultra-Lightweight Network for Multimodal Sleep Stage Scoring
arXiv:2602.23852v1 Announce Type: new Abstract: Automatic sleep stage scoring is crucial for the diagnosis and treatment of sleep disorders. Although deep learning models have advanced the field, many existing models are computationally demanding and designed for single-channel electroencephalography (EEG), limiting...
Court sides with parents in dispute over California policies on transgender students
The Supreme Court on Monday night granted a request from a group of California parents to reinstate a ruling by a federal district court that prohibits schools in that state […]The postCourt sides with parents in dispute over California policies...
Supreme Court grants Republicans’ request to pause order to redraw New York congressional map
The Supreme Court on Monday night cleared the way for New York to go forward with the 2026 elections using the state’s existing congressional map. Over the objections of the […]The postSupreme Court grants Republicans’ request to pause order to...
Court turns down several cases, including on filing fees for indigent prisoners and ability of felons to possess guns
Over the objections of the court’s three Democratic appointees, the Supreme Court on Monday morning declined to hear a case involving the payment of filing fees by indigent prisoners. The […]The postCourt turns down several cases, including on filing fees...
Birthright citizenship: A note on foundlings and comments on four complementary amicus briefs
Foundlings – babies born of unknown parentage – loomed large in the imagination of mid-19th century Americans, who dutifully read their Bibles and thought about baby Moses in a basket. […]The postBirthright citizenship: A note on foundlings and comments on...
Supreme Court skeptical of law banning drug users from possessing firearms
The Supreme Court on Monday was skeptical that the indictment of a Texas man on charges that he violated a federal law prohibiting the possession of a gun by the […]The postSupreme Court skeptical of law banning drug users from...
Justices to consider breadth of a federal defendant’s waiver of appeal
In Hunter v. United States, to be argued on Tuesday, March 3, the Supreme Court will address how broad federal defendants’ waivers of their right to appeal can be and […]The postJustices to consider breadth of a federal defendant’s waiver...
Trump FCC's equal-time crackdown doesn't apply equally—or at all—to talk radio
FCC Chairman Brendan Carr's unequal enforcement of the equal-time rule.
No one has a good plan for how AI companies should work with the government
As OpenAI transitions from a wildly successful consumer startup into a piece of national security infrastructure, the company seems unequipped to manage its new responsibilities.
First Amendment Inversion
Introduction A new arrangement of First Amendment positions has upturned constitutional discourse in key areas. Familiar perspectives have transposed not only in Supreme Court opinions but also in policymaking and public debate—and some are reverting back. Inversion on important questions...
Academic Freedom by Other Names: Historical Foundations for the First Amendment Right
Introduction The Supreme Court has stated that academic freedom is a “special concern” of the First Amendment.[1] Yet before 1957, there were no American legal precedents that recognized academic freedom as a component of the First Amendment. But these protections...
DMCD: Semantic-Statistical Framework for Causal Discovery
arXiv:2602.20333v1 Announce Type: new Abstract: We present DMCD (DataMap Causal Discovery), a two-phase causal discovery framework that integrates LLM-based semantic drafting from variable metadata with statistical validation on observational data. In Phase I, a large language model proposes a sparse...
KairosVL: Orchestrating Time Series and Semantics for Unified Reasoning
arXiv:2602.20494v1 Announce Type: new Abstract: Driven by the increasingly complex and decision-oriented demands of time series analysis, we introduce the Semantic-Conditional Time Series Reasoning task, which extends conventional time series analysis beyond purely numerical modeling to incorporate contextual and semantic...
CausalReasoningBenchmark: A Real-World Benchmark for Disentangled Evaluation of Causal Identification and Estimation
arXiv:2602.20571v1 Announce Type: new Abstract: Many benchmarks for automated causal inference evaluate a system's performance based on a single numerical output, such as an Average Treatment Effect (ATE). This approach conflates two distinct steps in causal analysis: identification-formulating a valid...
Online Algorithms with Unreliable Guidance
arXiv:2602.20706v1 Announce Type: new Abstract: This paper introduces a new model for ML-augmented online decision making, called online algorithms with unreliable guidance (OAG). This model completely separates between the predictive and algorithmic components, thus offering a single well-defined analysis framework...
ICON: Indirect Prompt Injection Defense for Agents based on Inference-Time Correction
arXiv:2602.20708v1 Announce Type: new Abstract: Large Language Model (LLM) agents are susceptible to Indirect Prompt Injection (IPI) attacks, where malicious instructions in retrieved content hijack the agent's execution. Existing defenses typically rely on strict filtering or refusal mechanisms, which suffer...
Natural Language Processing Models for Robust Document Categorization
arXiv:2602.20336v1 Announce Type: new Abstract: This article presents an evaluation of several machine learning methods applied to automated text classification, alongside the design of a demonstrative system for unbalanced document categorization and distribution. The study focuses on balancing classification accuracy...
fEDM+: A Risk-Based Fuzzy Ethical Decision Making Framework with Principle-Level Explainability and Pluralistic Validation
arXiv:2602.21746v1 Announce Type: new Abstract: In a previous work, we introduced the fuzzy Ethical Decision-Making framework (fEDM), a risk-based ethical reasoning architecture grounded in fuzzy logic. The original model combined a fuzzy Ethical Risk Assessment module (fERA) with ethical decision...
Make Every Draft Count: Hidden State based Speculative Decoding
arXiv:2602.21224v1 Announce Type: cross Abstract: Speculative decoding has emerged as a pivotal technique to accelerate LLM inference by employing a lightweight draft model to generate candidate tokens that are subsequently verified by the target model in parallel. However, while this...
Transborder Speech
ARTICLE Transborder Speech Ronald J. Krotoszynski, Jr.* In an increasingly globalized marketplace of ideas, First Amendment law and theory must recognize that the freedom of speech does not end at the water’s edge. Simply put, the locus of expressive activity...
Fintech Regulation 2026: Navigating the New Compliance Landscape
The regulatory environment for fintech has evolved dramatically, with new frameworks addressing digital assets, open banking, and AI-driven financial services.
The Mean is the Mirage: Entropy-Adaptive Model Merging under Heterogeneous Domain Shifts in Medical Imaging
arXiv:2602.21372v1 Announce Type: cross Abstract: Model merging under unseen test-time distribution shifts often renders naive strategies, such as mean averaging unreliable. This challenge is especially acute in medical imaging, where models are fine-tuned locally at clinics on private data, producing...
How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?
arXiv:2602.22441v1 Announce Type: new Abstract: Latent reasoning has been recently proposed as a reasoning paradigm and performs multi-step reasoning through generating steps in the latent space instead of the textual space. This paradigm enables reasoning beyond discrete language tokens by...