Foundation World Models for Agents that Learn, Verify, and Adapt Reliably Beyond Static Environments
arXiv:2602.23997v1 Announce Type: new Abstract: The next generation of autonomous agents must not only learn efficiently but also act reliably and adapt their behavior in open worlds. Standard approaches typically assume fixed tasks and environments with little or no novelty,...
InfoNCE Induces Gaussian Distribution
arXiv:2602.24012v1 Announce Type: new Abstract: Contrastive learning has become a cornerstone of modern representation learning, allowing training with massive unlabeled data for both task-specific and general (foundation) models. A prototypical loss in contrastive training is InfoNCE and its variants. In...
pathsig: A GPU-Accelerated Library for Truncated and Projected Path Signatures
arXiv:2602.24066v1 Announce Type: new Abstract: Path signatures provide a rich representation of sequential data, with strong theoretical guarantees and good performance in a variety of machine-learning tasks. While signatures have progressed from fixed feature extractors to trainable components of machine-learning...
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...
SCOTUStoday for Monday, March 2
If you are looking for a great introduction to this morning’s argument in United States v. Hemani, please check out this animated explainer, done in partnership with Briefly. Our live […]The postSCOTUStoday for Monday, March 2appeared first onSCOTUSblog.
Cursor has reportedly surpassed $2B in annualized revenue
The four-year-old startup saw its revenue run rate double over the past three months, according to one Bloomberg source.
Investors spill what they aren’t looking for anymore in AI SaaS companies
TechCrunch spoke with VCs to learn what investors aren't looking for in AI SaaS startups anymore.
Right Diagnosis, Wrong Cure: Reconceptualizing the Commerce Clause Basis for the Federal Prohibition on Felon Firearm Possession
Introduction Jonathan Adler recently posted the provocative piece: “Is the Federal Prohibition on Felon Firearm Possession Constitutional?”[1] Although Second Amendment challenges are all the rage, Adler instead asks about Congress’s commerce power. This Essay takes up Adler’s challenge to reconceptualize...
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...
Expressive Association as Shield, not Sword: A Constitutional Defense of DEI
Introduction Diversity, equity, and inclusion (DEI)—an effort aimed at remedying historic inequality in opportunities—faces the chopping block. Its opposition claims it commits the very sin it aimed to rid: discrimination. DEI’s opposition has mobilized and attacked on all fronts, already...
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...
Multilevel Determinants of Overweight and Obesity Among U.S. Children Aged 10-17: Comparative Evaluation of Statistical and Machine Learning Approaches Using the 2021 National Survey of Children's Health
arXiv:2602.20303v1 Announce Type: new Abstract: Background: Childhood and adolescent overweight and obesity remain major public health concerns in the United States and are shaped by behavioral, household, and community factors. Their joint predictive structure at the population level remains incompletely...
An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language models
arXiv:2602.20324v1 Announce Type: new Abstract: Phenotyping is fundamental to rare disease diagnosis, but manual curation of structured phenotypes from clinical notes is labor-intensive and difficult to scale. Existing artificial intelligence approaches typically optimize individual components of phenotyping but do not...
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...
Diffusion Modulation via Environment Mechanism Modeling for Planning
arXiv:2602.20422v1 Announce Type: new Abstract: Diffusion models have shown promising capabilities in trajectory generation for planning in offline reinforcement learning (RL). However, conventional diffusion-based planning methods often fail to account for the fact that generating trajectories in RL requires unique...
Learning to Rewrite Tool Descriptions for Reliable LLM-Agent Tool Use
arXiv:2602.20426v1 Announce Type: new Abstract: The performance of LLM-based agents depends not only on the agent itself but also on the quality of the tool interfaces it consumes. While prior work has focused heavily on agent fine-tuning, tool interfaces-including natural...
PreScience: A Benchmark for Forecasting Scientific Contributions
arXiv:2602.20459v1 Announce Type: new Abstract: Can AI systems trained on the scientific record up to a fixed point in time forecast the scientific advances that follow? Such a capability could help researchers identify collaborators and impactful research directions, and anticipate...
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...
Inner Speech as Behavior Guides: Steerable Imitation of Diverse Behaviors for Human-AI coordination
arXiv:2602.20517v1 Announce Type: new Abstract: Effective human-AI coordination requires artificial agents capable of exhibiting and responding to human-like behaviors while adapting to changing contexts. Imitation learning has emerged as one of the prominent approaches to build such agents by training...
From Logs to Language: Learning Optimal Verbalization for LLM-Based Recommendation in Production
arXiv:2602.20558v1 Announce Type: new Abstract: Large language models (LLMs) are promising backbones for generative recommender systems, yet a key challenge remains underexplored: verbalization, i.e., converting structured user interaction logs into effective natural language inputs. Existing methods rely on rigid templates...
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...
Physics-based phenomenological characterization of cross-modal bias in multimodal models
arXiv:2602.20624v1 Announce Type: new Abstract: The term 'algorithmic fairness' is used to evaluate whether AI models operate fairly in both comparative (where fairness is understood as formal equality, such as "treat like cases as like") and non-comparative (where unfairness arises...
When can we trust untrusted monitoring? A safety case sketch across collusion strategies
arXiv:2602.20628v1 Announce Type: new Abstract: AIs are increasingly being deployed with greater autonomy and capabilities, which increases the risk that a misaligned AI may be able to cause catastrophic harm. Untrusted monitoring -- using one untrusted model to oversee another...
Identifying two piecewise linear additive value functions from anonymous preference information
arXiv:2602.20638v1 Announce Type: new Abstract: Eliciting a preference model involves asking a person, named decision-maker, a series of questions. We assume that these preferences can be represented by an additive value function. In this work, we query simultaneously two decision-makers...
How Foundational Skills Influence VLM-based Embodied Agents:A Native Perspective
arXiv:2602.20687v1 Announce Type: new Abstract: Recent advances in vision-language models (VLMs) have shown promise for human-level embodied intelligence. However, existing benchmarks for VLM-driven embodied agents often rely on high-level commands or discretized action spaces, which are non-native settings that differ...