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Differentially Private Preference Data Synthesis for Large Language Model Alignment

arXiv:2605.30808v1 Announce Type: cross Abstract: Preference alignment is a crucial post-training step for large language models (LLMs) to ensure their outputs align with human values. However, post-t

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DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation

DGX agent

arXiv:2506.11653v3 Announce Type: replace-cross Abstract: Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Ant

safetyarxiv-cs-ai

1 Jun 2026

Distilling LLM Feedback for Lean Theorem Proving

arXiv:2605.30861v1 Announce Type: new Abstract: Post-training for reasoning models typically combines supervised fine-tuning with reinforcement learning from verifiable rewards, most commonly with GRP

DiTTo: Scalable Order-aware All-in-One Image Restoration Agent

arXiv:2605.30915v1 Announce Type: new Abstract: Real-world images rarely suffer from a single degradation, and the order in which degradations are removed substantially affects the final restoration q

DOA: Training-Free Decoder-Only Attention Policy for Long-Form Simultaneous Translation with SpeechLLMs

arXiv:2605.31432v1 Announce Type: cross Abstract: Simultaneous speech-to-text translation (SimulST) generates translations while speech is still unfolding, requiring a streaming policy that decides wh

DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization

arXiv:2605.31455v1 Announce Type: cross Abstract: Large language models are increasingly deployed in multi-turn interactive settings where users or environments can iteratively provide lightweight fee

safetyarxiv-cs-cl

Dual Mechanisms of Value Expression: Intrinsic vs. Prompted Values in Large Language Models

arXiv:2509.24319v4 Announce Type: replace-cross Abstract: Large language models can express values in two main ways: (1) intrinsic expression, reflecting the model's inherent values learned during tra

EchoRL: Reinforcement Learning via Rollout Echoing

arXiv:2605.31228v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards is an effective route for post-training to strengthen the reasoning capability of large language models

Efficient and Uncertainty-Aware Diffusion Framework for Offline-to-Online Reinforcement Learning

arXiv:2605.30776v1 Announce Type: new Abstract: Offline-to-Online Reinforcement Learning (O2O-RL) leverages an offline, pre-trained policy to minimize costly online interactions. Although data-efficie

ELAN4D: Embodiment-Centric 4D Supervision for Vision-Language-Action Models via Plug-and-Play Adaptation

arXiv:2605.30484v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown promise for robotic manipulation, yet most existing policies operate reactively by directly regressing ac

Elon was right that what OpenAI did in its for profit turn was shameful. But what he is doing with the SpaceX, at the likely expense of many…

Elon was right that what OpenAI did in its for profit turn was shameful. But what he is doing with the SpaceX, at the likely expense of many people’s retirement funds, is just as shameful. SpaceX bein

Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market

arXiv:2605.30363v1 Announce Type: cross Abstract: Regime shifts in financial markets reorganise the joint dynamics of asset prices and macro variables, breaking any single-regime calibration. They are

Entropic Projection Alignment: Estimating, Explaining, and Improving Model Performance Under Distribution Shift

arXiv:2605.31250v1 Announce Type: cross Abstract: We propose a unified framework for addressing three key challenges of distribution shift: (1) estimating a model's performance on an unlabeled target

Envisioning Beyond the Few: Disentangled Semantics and Primitives for Few-Shot Atypical Layout-to-Image Generation

arXiv:2605.31266v1 Announce Type: cross Abstract: The layout-to-image (L2I) task enables fine-grained control over image generation via object categories and spatial layouts. However, existing L2I met

Equivariant Latent Alignment via Flow Matching under Group Symmetries

arXiv:2605.30705v1 Announce Type: new Abstract: Geometry-aware generative models and novel view synthesis approaches have shown strong potential in visual fidelity and consistency. In parallel, equiva

Extending the UXR Point of View Pyramid: A Generative AI-Augmented Methodology for Human-Centred AI Systems

arXiv:2605.31143v1 Announce Type: cross Abstract: Rising household debt and cost-of-living pressures in the United Kingdom have intensified the role of AI-driven financial technologies in mediating cr

Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency

arXiv:2602.07285v2 Announce Type: replace Abstract: Binary classification based on predicted probabilities (scores) is a fundamental task in supervised machine learning. While thresholding scores is B

Feat2Go: Visual Feature-Grounded Value Estimation for Embodied Reinforcement Learning

arXiv:2605.30795v1 Announce Type: new Abstract: Reinforcement learning is a promising approach for improving the capabilities of vision-language-action (VLA) models while avoiding the heavy data requi

Feature-Optimized Vision for Adaptive 3D Scene Reconstruction

arXiv:2605.31534v1 Announce Type: cross Abstract: Three-dimensional scene reconstruction depends on local image evidence that is both visually discriminative and geometrically useful. Fixed feature th

FLAG: Flow Policy MaxEnt-RL by Latent Augmented Guidance

arXiv:2605.30749v1 Announce Type: new Abstract: Maximum entropy reinforcement learning (MaxEnt-RL) enables robust exploration, yet practical implementations often restrict policies to simple Gaussians

Florida AG James Uthmeier sues OpenAI and Sam Altman, seeking to hold Altman personally liable for deceptive trade practices, negligence, and public nuisance (NBC News)

NBC News: Florida AG James Uthmeier sues OpenAI and Sam Altman, seeking to hold Altman personally liable for deceptive trade practices, negligence, and public nuisance — Florida's seeks to hold Sam Al

safetytechmeme

Forecasting with Hyper-Trees

arXiv:2405.07836v5 Announce Type: replace Abstract: We introduce Hyper-Trees as a novel framework for modeling time series data using gradient boosted trees. Unlike conventional tree-based approaches

GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring

arXiv:2605.30865v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) provides a dense view of daily metabolic physiology, yet existing generic time-series and CGM-specific foundation mo

Hamiltonian-Inspired Attention Mechanism for Scalable RF Transmitter Fingerprinting

arXiv:2605.30364v1 Announce Type: cross Abstract: Radio-frequency (RF) fingerprinting identifies wire-less transmitters using hardware-induced imperfections present in baseband I/Q signals. However, d

HARP-VLA: Human-Robot Aligned Representation Learning for Vision-Language-Action Model

arXiv:2605.31234v1 Announce Type: new Abstract: Learning generalizable vision-language-action (VLA) models from large-scale human videos is promising but challenging due to cross-embodiment discrepanc

Healthcare Mechanisms from Policy-as-Code Search under Strategic Provider Response

arXiv:2605.30680v1 Announce Type: new Abstract: Healthcare mechanisms are inseparable from the strategic provider response they induce: existing healthcare AI benchmarks hold this response fixed and s

HiPER: Hierarchical Reinforcement Learning with Explicit Credit Assignment for Large Language Model Agents

arXiv:2602.16165v2 Announce Type: replace-cross Abstract: Training LLMs as interactive agents for multi-turn decision-making remains challenging, particularly in long-horizon tasks with sparse and del

HQ-JEPA: Hybrid Quantum Joint-Embedding Predictive Architecture for Cross-Modal Remote Sensing Representation Learning

arXiv:2605.31068v1 Announce Type: new Abstract: We introduce HQ-JEPA, a hybrid quantum-classical joint-embedding predictive architecture for cross-modal remote sensing representation learning. The pro

Human-Alignment and Calibration of Inference-Time Uncertainty in Large Language Models

arXiv:2508.08204v2 Announce Type: replace-cross Abstract: There has been much recent interest in evaluating large language models for uncertainty calibration to facilitate model control and modulate u

Human-Alignment, Calibration, and Activation Patterns in Large Language Model Uncertainty

arXiv:2605.30675v1 Announce Type: cross Abstract: Uncertainty Quantification is a large and growing subfield of large language model behavioral analysis. Primarily to recognize and combat hallucinatio

Human Psychometric Questionnaires Mischaracterize LLM Behavior

arXiv:2509.10078v4 Announce Type: replace-cross Abstract: We examine whether human psychometric questionnaires can serve as reliable tools for characterizing and predicting LLM behavior in everyday us

I would say that it is absurd to say that “AI belongs to the people”, when so many companies have worked so hard to develop it, but it is al…

I would say that it is absurd to say that “AI belongs to the people”, when so many companies have worked so hard to develop it, but it is also absurd that Generative AI has basically been built on the

IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning

arXiv:2602.19049v2 Announce Type: replace Abstract: Large language models increasingly rely on long chains of thought to improve accuracy, yet such gains come with substantial inference-time costs. We

safetyarxiv-cs-cl

If “Insanity is doing the same thing over and over again and expecting different results”, what the heck is Generative AI?

Gary Marcus critiques generative AI by applying the 'insanity' aphorism to highlight repetitive patterns in how these systems operate—suggesting they may be fundamentally limited by repeating the same

ImmersiveTTS: Environment-Aware Text-to-Speech with Multimodal Diffusion Transformer and Domain-Specific Representation Alignment

arXiv:2605.30965v1 Announce Type: cross Abstract: Recent advancements in text-guided audio generation have yielded promising results in diverse domains, including sound effects, speech, and music. How

IsoCLIP: Decomposing CLIP Projectors for Efficient Intra-modal Alignment

arXiv:2603.19862v2 Announce Type: replace Abstract: Vision-Language Models like CLIP are extensively used for inter-modal tasks which involve both visual and text modalities. However, when the individ

Kiss your pensions goodbye, folks May 20 - SpaceX's (SPCX) S-1 filing Ludicrous targeted valuation: 1.8T despite 4.28B loss over last year…

Kiss your pensions goodbye, folks May 20 - SpaceX's (SPCX) S-1 filing Ludicrous targeted valuation: 1.8T despite 4.28B loss over last year June 11 - offering price set June 12 - first day of trading /

LARK: Learnability-Grounded Trajectory Selection for Efficient Reasoning Distillation

arXiv:2605.30651v1 Announce Type: cross Abstract: We study trajectory selection for reasoning distillation, where teacher-generated reasoning trajectories are selectively used as supervision for a stu

Learning Controlled Separation of Small Objects Between Two Fingers with a Tactile Skin

arXiv:2605.31486v1 Announce Type: new Abstract: We introduce and solve the novel task of controlled separation of small objects with two fingers of a multi-purpose robotic hand: after grasping into a

Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt

arXiv:2505.20795v2 Announce Type: replace Abstract: Recent robot learning methods commonly rely on imitation learning from massive robotic dataset collected with teleoperation. When facing a new task,

Learning Terrain-Aware Whole-Body Control for Perceptive Legged Loco-Manipulation

arXiv:2605.31343v1 Announce Type: new Abstract: Legged manipulators integrate exceptional terrain adaptability along with mobile manipulation capabilities, which make them highly promising for deploym

Lightweight CNN-Based Anomaly Detection for High Voltage Converter Modulators in the Spallation Neutron Source

arXiv:2605.31259v1 Announce Type: new Abstract: Unscheduled trips of high-power pulsed converters are a leading source of downtime at large accelerator facilities. At the Spallation Neutron Source (SN

LVSA: Training-Free Sparse Attention for Long Video Diffusion

arXiv:2605.31057v1 Announce Type: new Abstract: Dense self-attention is the compute and quality bottleneck of long-video diffusion inference: cost grows quadratically with the sequence length, and bey

Mental Damage: Caption Poisoning Attacks on Retrieval-Augmented Text-to-Music Generation

arXiv:2605.30365v1 Announce Type: cross Abstract: Retrieval-augmented text-to-music (TTM) systems augment underspecified user prompts using captions retrieved from a music caption dataset. This design

MergeTok: Unified Continuous and Discrete Visual Tokenization via Token Merging

arXiv:2605.30904v1 Announce Type: new Abstract: Most visual tokenizers for image generation are bifurcated into two families with complementary limitations: continuous VAEs offer high-fidelity reconst

Multi-Agent Teams Hold Experts Back

arXiv:2602.01011v4 Announce Type: replace-cross Abstract: Multi-agent LLM systems are increasingly deployed as autonomous collaborators, where agents interact freely rather than execute fixed, pre-spe

Neuron-Level Interventions for Gendered and Gender-Neutral Generation in Language Models

arXiv:2605.30717v1 Announce Type: new Abstract: Language models (LMs) can produce gendered language and stereotypes even when given neutral prompts. Most prior work on gender bias in LMs primarily exa

safetyarxiv-cs-cl

Neurosymbolic rising!

Neurosymbolic rising! I've wanted to work on deep neurosymbolic integration for a while: if you make an 800k transformer reason *like* a logical solver, you get 100% on sudoku-extreme w. 15m of train