Conditional Sampling via Wasserstein Autoencoders and Triangular Transport
arXiv:2604.02644v1 Announce Type: new Abstract: We present Conditional Wasserstein Autoencoders (CWAEs), a framework for conditional simulation that exploits low-dimensional structure in both the conditioned and the conditioning variables. The key idea is to modify a Wasserstein autoencoder to use a...
SocioEval: A Template-Based Framework for Evaluating Socioeconomic Status Bias in Foundation Models
arXiv:2604.02660v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly power decision-making systems across critical domains, understanding and mitigating their biases becomes essential for responsible AI deployment. Although bias assessment frameworks have proliferated for attributes such as race and...
What oral argument told us in the birthright citizenship case
Empirical SCOTUS is a recurring series by Adam Feldman that looks at Supreme Court data, primarily in the form of opinions and oral arguments, to provide insights into the justices’ decision making and […]The postWhat oral argument told us in...
OpenAI executive shuffle includes new role for COO Brad Lightcap to lead ‘special projects’
In addition to Lightcap's new role, OpenAI CMO Kate Rouch will be stepping away from the company to focus on cancer recovery, with a plan to return when her health allows.
The Privileges or Immunities Clause, Abridged: A Critique of Kurt Lash on the Fourteenth Amendment
ARTICLE The Privileges or Immunities Clause, Abridged: A Critique of Kurt Lash on the Fourteenth Amendment Randy E. Barnett* & Evan D. Bernick** The Privileges or Immunities Clause of the Fourteenth Amendment reads: “No State shall make or enforce any...
The Enumerated-Rights Reading of the Privileges or Immunities Clause: A Response to Barnett and Bernick
ARTICLE The Enumerated-Rights Reading of the Privileges or Immunities Clause: A Response to Barnett and Bernick Kurt T. Lash* In 1871, John Bingham explained the meaning of the Fourteenth Amendment’s Privileges or Immunities Clause—a clause Bingham himself drafted and had...
Agent Q-Mix: Selecting the Right Action for LLM Multi-Agent Systems through Reinforcement Learning
arXiv:2604.00344v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown remarkable performance in completing various tasks. However, solving complex problems often requires the coordination of multiple agents, raising a fundamental question: how to effectively select and interconnect these agents....
Frege in the Flesh: Biolinguistics and the Neural Enforcement of Syntactic Structures
arXiv:2604.00291v1 Announce Type: new Abstract: Biolinguistics is the interdisciplinary scientific study of the biological foundations, evolution, and genetic basis of human language. It treats language as an innate biological organ or faculty of the mind, rather than a cultural tool,...
Can Large Language Models Self-Correct in Medical Question Answering? An Exploratory Study
arXiv:2604.00261v2 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance on medical question answering (medical QA), and chain-of-thought (CoT) prompting has further improved results by eliciting explicit intermediate reasoning; meanwhile, self-reflective (self-corrective) prompting has been widely claimed...
LLM Essay Scoring Under Holistic and Analytic Rubrics: Prompt Effects and Bias
arXiv:2604.00259v1 Announce Type: new Abstract: Despite growing interest in using Large Language Models (LLMs) for educational assessment, it remains unclear how closely they align with human scoring. We present a systematic evaluation of instruction-tuned LLMs across three open essay-scoring datasets...
In harmony with gpt-oss
arXiv:2604.00362v1 Announce Type: new Abstract: No one has independently reproduced OpenAI's published scores for gpt-oss-20b with tools, because the original paper discloses neither the tools nor the agent harness. We reverse-engineered the model's in-distribution tools: when prompted without tool definitions,...
Improvisational Games as a Benchmark for Social Intelligence of AI Agents: The Case of Connections
arXiv:2604.00284v1 Announce Type: new Abstract: We formally introduce a improvisational wordplay game called Connections to explore reasoning capabilities of AI agents. Playing Connections combines skills in knowledge retrieval, summarization and awareness of cognitive states of other agents. We show how...
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...
Supreme Court appears likely to side against Trump on birthright citizenship
Updated on April 1 at 10:10 p.m. On Jan. 20, 2025, President Donald Trump signed an executive order that would end birthright citizenship – the guarantee of U.S. citizenship to […]The postSupreme Court appears likely to side against Trump on...
Finding and Reactivating Post-Trained LLMs' Hidden Safety Mechanisms
arXiv:2604.00012v1 Announce Type: cross Abstract: Despite the impressive performance of general-purpose large language models (LLMs), they often require fine-tuning or post-training to excel at specific tasks. For instance, large reasoning models (LRMs), such as the DeepSeek-R1 series, demonstrate strong reasoning...
Think Twice Before You Write -- an Entropy-based Decoding Strategy to Enhance LLM Reasoning
arXiv:2604.00018v1 Announce Type: cross Abstract: Decoding strategies play a central role in shaping the reasoning ability of large language models (LLMs). Traditional methods such as greedy decoding and beam search often suffer from error propagation, while sampling-based approaches introduce randomness...
Matching Accuracy, Different Geometry: Evolution Strategies vs GRPO in LLM Post-Training
arXiv:2604.01499v1 Announce Type: new Abstract: Evolution Strategies (ES) have emerged as a scalable gradient-free alternative to reinforcement learning based LLM fine-tuning, but it remains unclear whether comparable task performance implies comparable solutions in parameter space. We compare ES and Group...
Retrospective on PAT x ICML 2026 AI Paper Assistant Program
Trump defunding of NPR and PBS blocked by judge, but damage is already done
Judge invalidates Trump executive order, but Congress also cut off all funding.
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...
Agent psychometrics: Task-level performance prediction in agentic coding benchmarks
arXiv:2604.00594v1 Announce Type: new Abstract: As the focus in LLM-based coding shifts from static single-step code generation to multi-step agentic interaction with tools and environments, understanding which tasks will challenge agents and why becomes increasingly difficult. This is compounded by...
DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data
arXiv:2604.01481v1 Announce Type: new Abstract: The development of robust clinical decision support systems is frequently impeded by the scarcity of high-fidelity, privacy-preserving biomedical data. While Generative Large Language Models (LLMs) offer a promising avenue for synthetic data generation, they often...
What’s new for the Position Paper Track at NeurIPS 2026
Collaborative AI Agents and Critics for Fault Detection and Cause Analysis in Network Telemetry
arXiv:2604.00319v1 Announce Type: new Abstract: We develop algorithms for collaborative control of AI agents and critics in a multi-actor, multi-critic federated multi-agent system. Each AI agent and critic has access to classical machine learning or generative AI foundation models. The...
Towards Reliable Truth-Aligned Uncertainty Estimation in Large Language Models
arXiv:2604.00445v1 Announce Type: new Abstract: Uncertainty estimation (UE) aims to detect hallucinated outputs of large language models (LLMs) to improve their reliability. However, UE metrics often exhibit unstable performance across configurations, which significantly limits their applicability. In this work, we...
Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method
arXiv:2604.01279v1 Announce Type: new Abstract: We introduce Sven (Singular Value dEsceNt), a new optimization algorithm for neural networks that exploits the natural decomposition of loss functions into a sum over individual data points, rather than reducing the full loss to...
Trump attends birthright citizenship argument
Updated on April 1 at 7:48 p.m. As soon as President Donald Trump last evening mentioned attending argument in the birthright citizenship case in Trump v. Barbara today, some Supreme […]The postTrump attends birthright citizenship argumentappeared first onSCOTUSblog.
Learning ECG Image Representations via Dual Physiological-Aware Alignments
arXiv:2604.01526v1 Announce Type: new Abstract: Electrocardiograms (ECGs) are among the most widely used diagnostic tools for cardiovascular diseases, and a large amount of ECG data worldwide appears only in image form. However, most existing automated ECG analysis methods rely on...
Preference Guided Iterated Pareto Referent Optimisation for Accessible Route Planning
arXiv:2604.00795v1 Announce Type: new Abstract: We propose the Preference Guided Iterated Pareto Referent Optimisation (PG-IPRO) for urban route planning for people with different accessibility requirements and preferences. With this algorithm the user can interact with the system by giving feedback...