Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
arXiv:2604.01345v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) recovers the loss function of a forward learner from its observed responses adaptive IRL aims to reconstruct the loss function of a forward learner by passively observing its gradients as it...
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OpenAI, not yet public, raises $3B from retail investors in monster $122B fund raise
OpenAI's latest funding round, led by Amazon, Nvidia, and SoftBank, values the AI lab at $852 billion as it nears an IPO.
Criterion Validity of LLM-as-Judge for Business Outcomes in Conversational Commerce
arXiv:2604.00022v1 Announce Type: cross Abstract: Multi-dimensional rubric-based dialogue evaluation is widely used to assess conversational AI, yet its criterion validity -- whether quality scores are associated with the downstream outcomes they are meant to serve -- remains largely untested. We...
SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
arXiv:2604.01337v1 Announce Type: new Abstract: While deep learning has significantly advanced accident anticipation, the robustness of these safety-critical systems against real-world perturbations remains a major challenge. We reveal that state-of-the-art models like CRASH, despite their high performance, exhibit significant instability...
A Reliability Evaluation of Hybrid Deterministic-LLM Based Approaches for Academic Course Registration PDF Information Extraction
arXiv:2604.00003v1 Announce Type: cross Abstract: This study evaluates the reliability of information extraction approaches from KRS documents using three strategies: LLM only, Hybrid Deterministic - LLM (regex + LLM), and a Camelot based pipeline with LLM fallback. Experiments were conducted...
Large Language Models in the Abuse Detection Pipeline
arXiv:2604.00323v1 Announce Type: new Abstract: Online abuse has grown increasingly complex, spanning toxic language, harassment, manipulation, and fraudulent behavior. Traditional machine-learning approaches dependent on static classifiers and labor-intensive labeling struggle to keep pace with evolving threat patterns and nuanced policy...
Brevity Constraints Reverse Performance Hierarchies in Language Models
arXiv:2604.00025v1 Announce Type: new Abstract: Standard evaluation protocols reveal a counterintuitive phenomenon: on 7.7% of benchmark problems spanning five datasets, larger language models underperform smaller ones by 28.4 percentage points despite 10-100x more parameters. Through systematic evaluation of 31 models...
Variational LSTM with Augmented Inputs: Nonlinear Response History Metamodeling with Aleatoric and Epistemic Uncertainty
arXiv:2604.01587v1 Announce Type: new Abstract: Uncertainty propagation in high-dimensional nonlinear dynamic structural systems is pivotal in state-of-the-art performance-based design and risk assessment, where uncertainties from both excitations and structures, i.e., the aleatoric uncertainty, must be considered. This poses a significant...
TRIMS: Trajectory-Ranked Instruction Masked Supervision for Diffusion Language Models
arXiv:2604.00666v1 Announce Type: new Abstract: Diffusion language models (DLMs) offer a promising path toward low-latency generation through parallel decoding, but their practical efficiency depends heavily on the decoding trajectory. In practice, this advantage often fails to fully materialize because standard...
DDCL: Deep Dual Competitive Learning: A Differentiable End-to-End Framework for Unsupervised Prototype-Based Representation Learning
arXiv:2604.01740v1 Announce Type: new Abstract: A persistent structural weakness in deep clustering is the disconnect between feature learning and cluster assignment. Most architectures invoke an external clustering step, typically k-means, to produce pseudo-labels that guide training, preventing the backbone from...
Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler
arXiv:2604.01870v1 Announce Type: new Abstract: In modern process industries, data-driven models are important tools for real-time monitoring when key performance indicators are difficult to measure directly. While accurate predictions are essential, reliable uncertainty quantification (UQ) is equally critical for safety,...
Cognichip wants AI to design the chips that power AI, and just raised $60M to try
The firm says it can reduce the cost of chip development by more than 75% and cut the timeline by more than half.
Robust Graph Representation Learning via Adaptive Spectral Contrast
arXiv:2604.01878v1 Announce Type: new Abstract: Spectral graph contrastive learning has emerged as a unified paradigm for handling both homophilic and heterophilic graphs by leveraging high-frequency components. However, we identify a fundamental spectral dilemma: while high-frequency signals are indispensable for encoding...
Dynin-Omni: Omnimodal Unified Large Diffusion Language Model
arXiv:2604.00007v1 Announce Type: cross Abstract: We present Dynin-Omni, the first masked-diffusion-based omnimodal foundation model that unifies text, image, and speech understanding and generation, together with video understanding, within a single architecture. Unlike autoregressive unified models that serialize heterogeneous modalities, or...
How Do Language Models Process Ethical Instructions? Deliberation, Consistency, and Other-Recognition Across Four Models
arXiv:2604.00021v1 Announce Type: cross Abstract: Alignment safety research assumes that ethical instructions improve model behavior, but how language models internally process such instructions remains unknown. We conducted over 600 multi-agent simulations across four models (Llama 3.3 70B, GPT-4o mini, Qwen3-Next-80B-A3B,...
Training In-Context and In-Weights Mixtures Via Contrastive Context Sampling
arXiv:2604.01601v1 Announce Type: new Abstract: We investigate training strategies that co-develop in-context learning (ICL) and in-weights learning (IWL), and the ability to switch between them based on context relevance. Although current LLMs exhibit both modes, standard task-specific fine-tuning often erodes...
Court appears sympathetic to death-row inmate’s attempt to challenge racial discrimination in jury selection
The Supreme Court on Tuesday seemed sympathetic to a Mississippi man who argues that a district attorney violated the Constitution’s ban on racial discrimination in jury selection. Terry Pitchford is […]The postCourt appears sympathetic to death-row inmate’s attempt to challenge...
"Who Am I, and Who Else Is Here?" Behavioral Differentiation Without Role Assignment in Multi-Agent LLM Systems
arXiv:2604.00026v1 Announce Type: new Abstract: When multiple large language models interact in a shared conversation, do they develop differentiated social roles or converge toward uniform behavior? We present a controlled experimental platform that orchestrates simultaneous multi-agent discussions among 7 heterogeneous...
Agentic AI -- Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data
arXiv:2603.05735v2 Announce Type: cross Abstract: We present an AI agentic measurement of the thrust distribution in $e^{+}e^{-}$ collisions at $\sqrt{s}=91.2$~GeV using archived ALEPH data. The analysis and all note writing is carried out entirely by AI agents (OpenAI Codex and...
The Chronicles of RiDiC: Generating Datasets with Controlled Popularity Distribution for Long-form Factuality Evaluation
arXiv:2604.00019v1 Announce Type: cross Abstract: We present a configurable pipeline for generating multilingual sets of entities with specified characteristics, such as domain, geographical location and popularity, using data from Wikipedia and Wikidata. These datasets are intended for evaluating the factuality...
Defending the Bankrupt Castle
Every year, hundreds of thousands of Americans file for Chapter 7 bankruptcy. In each case, the U.S. Department of Justice appoints a private individual, usually an attorney, to serve as the bankruptcy trustee and administer the estate. Equipped with significant...
Birthright citizenship: Hintopoulos, Harlan II, and “Joltin’ Joe” – mid-century elements of American greatness worth remembering on the eve of Barbara
“Of course.” “No one wants to change that.” As mid-20th century American leaders both on and off the Supreme Court pondered America’s place in a brutish world, these are the […]The postBirthright citizenship: Hintopoulos, Harlan II, and “Joltin’ Joe” –...
Court to hear argument on claim of racial discrimination in jury selection
The Supreme Court will hear oral argument on Tuesday in Pitchford v. Cain, the case of a Mississippi man who contends that he was sentenced to death in violation of […]The postCourt to hear argument on claim of racial discrimination...
The key arguments in the birthright citizenship case
On April 1, the Supreme Court will hear oral arguments in one of the highest-profile cases of the 2025-26 term – and indeed, one of the biggest cases in several […]The postThe key arguments in the birthright citizenship caseappeared first...
Court repudiates extension of federal supervised release while a defendant absconds
After completing a term of imprisonment, federal criminal defendants often serve terms of supervised release that usually last between one to five years, depending on the offense for which they […]The postCourt repudiates extension of federal supervised release while a...
Statement: Head of US Policy on the White House AI legislative recommendations
The White House published it’s long-awaited AI legislative recommendations on Friday, and it still includes a call for Congress to […]
“This is What it Means to be Pro-Human” Declares Broad Coalition of Conservative, Progressive, and Civil Society Groups in Statement of Shared Principles on AI
Amid a rising backlash to Silicon Valley overreach, a remarkably diverse group from across the political spectrum announced a set of AI principles to clearly define the goals of the emerging pro-human movement.
AI Company Safety Practices Fall Short of Public Commitments and Show Structural Weaknesses, as Top Performers Widen the Gap
But in a win for transparency, five leading companies participated in the scorecard's survey for the first time, providing critical new information to the public.
Judge irate as defendant joins by Zoom while driving—then lies about it
"Let me see the driver!"