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Modality Alignment across Trees on Heterogeneous Hyperbolic Manifolds

arXiv:2510.27391v2 Announce Type: replace Abstract: Modality alignment is critical for vision-language models (VLMs) to effectively integrate information across modalities. However, existing methods e

Model Fusion via Retrofitting

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arXiv:2507.00037v2 Announce Type: replace-cross Abstract: Model fusion seeks to combine independently trained neural networks into a single model without retraining, but is complicated by representati

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29 May 2026

Modeling Hierarchical Thinking in Large Reasoning Models

arXiv:2510.22437v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) solve complex tasks by generating long Chain-of-Thought (CoT) sequences; however, the emergent dynamics governing reas

Modularizing Educational LLM-Agency for Fostering Responsible Learning Assistance

arXiv:2605.30187v1 Announce Type: new Abstract: The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large lang

MonoPhysics: Estimating Geometry, Appearance, and Physical Parameters from Monocular Videos

arXiv:2605.30320v1 Announce Type: new Abstract: Existing inverse physics methods recover physical parameters from multi-view videos, where geometric constraints across views resolve scale and 3D struc

Multi-Resolution End-to-End Deep Neural Network for Optimizing Latency-Accuracy Tradeoff in Autonomous Driving

arXiv:2605.29138v1 Announce Type: cross Abstract: Latency-accuracy tradeoffs are fundamental in real-time applications of deep neural networks (DNNs) for cyber-physical systems. In autonomous driving,

Multiple executives tell me they’re looking to decrease their AI expenses just as three major AI IPOs are on the horizon. My latest:

Multiple executives tell me they’re looking to decrease their AI expenses just as three major AI IPOs are on the horizon. My latest: CEOs are bargain hunting for AI https://www.axios.com/2026/05/29/ce

Native Audio-Visual Alignment for Generation

arXiv:2605.30073v1 Announce Type: new Abstract: Joint audio-video generation aims to synthesize temporally synchronized and semantically coherent visual-acoustic content. However, existing open-source

Neural Network Verification using Partial Multi-Neuron Relaxation

arXiv:2605.30155v1 Announce Type: cross Abstract: The increasing integration of deep neural networks in critical systems has spawned a theoretical and practical interest in formally guaranteeing safet

Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor

arXiv:2605.30277v1 Announce Type: new Abstract: Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular rea

Nobody knows for sure where employment is going and over what time frame. But one thing I can tell you for sure is that the big AI CEO’s hav…

Nobody knows for sure where employment is going and over what time frame. But one thing I can tell you for sure is that the big AI CEO’s have started lying about it. When they tell you know “we are ju

Note to all staff: Turns out that super tasty AI candy we've been putting out in large bowls isn't free and it isn't necessarily leading to …

Note to all staff: Turns out that super tasty AI candy we've been putting out in large bowls isn't free and it isn't necessarily leading to better products for our customers. From now on, all employee

Offline Multi-agent Reinforcement Learning via Sequential Score Decomposition

arXiv:2505.05968v3 Announce Type: replace Abstract: Offline cooperative multi-agent reinforcement learning (MARL) faces unique challenges due to distributional shifts, particularly stemming from the h

Offline Reinforcement Learning with Generative Trajectory Policies

arXiv:2510.11499v2 Announce Type: replace-cross Abstract: Generative models have emerged as a powerful class of policies for offline reinforcement learning (RL) due to their ability to capture complex

On the Geometry of Games and their Solvers

arXiv:2605.29919v1 Announce Type: new Abstract: A central challenge in game theory and learning systems such as GANs is understanding which algorithms can efficiently compute equilibria across the het

Online Fair Division with Additional Information

arXiv:2505.24503v3 Announce Type: replace-cross Abstract: We study the problem of fairly allocating indivisible goods to agents in an online setting, where goods arrive sequentially and must be alloca

Open Problem: Separating Geometric and Algorithmic Compression via Cayley-Table Completion

arXiv:2605.29885v1 Announce Type: new Abstract: Modern statistical learning theory and deep learning characterize generalization primarily in terms of continuous capacity control (e.g., norm-based reg

Opus 4.8 is insane, nothing will be the same after this model 💀

Gary Marcus expresses strong enthusiasm about Opus 4.8, suggesting it represents a significant breakthrough in AI capabilities. The post implies the model introduces substantial improvements or novel

Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation

arXiv:2605.29390v1 Announce Type: new Abstract: Text-to-image (T2I) models have become increasingly capable of generating high-quality images. Yet, enforcing the explicit absence of a specified object

Paper Agents, Paper Gains: An Empirical Analysis of DeFi Investment Agents

arXiv:2605.29174v1 Announce Type: new Abstract: DeFi investment agents, systems that use AI for autonomous on-chain trading, have attained over USD 3 billion in combined token valuations since late 20

Path-Space Mirror Descent for On-Policy Reinforcement Learning under the Generalized Schrodinger Bridge

arXiv:2603.21621v2 Announce Type: replace Abstract: Classical on-policy algorithms such as PPO and mirror descent policy optimization provide stable proximal policy updates through tractable action li

PEARL: Training Socratic Tutors with Pedagogically Aligned Reinforcement Learning

arXiv:2605.29582v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown promise as educational tutors, yet effective tutoring requires more than solving problems: it must provide pro

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Permutation-Invariant Spectral Learning via Dyson Diffusion

arXiv:2510.08535v2 Announce Type: replace-cross Abstract: Diffusion models are central to generative modeling and have been adapted to graphs by diffusing adjacency matrix representations. The challen

PersonaAgent: Bridging Memory and Action for Personalized LLM Agents

arXiv:2506.06254v2 Announce Type: replace Abstract: Large Language Model (LLM) empowered agents have recently emerged as advanced paradigms that exhibit impressive capabilities in a wide range of doma

Phase-Conditioned Imitation Learning with Autonomous Failure Recovery for Robust Deformable Object Manipulation

arXiv:2605.29407v1 Announce Type: new Abstract: This paper presents a phase-conditioned, force-aware framework for robust deformable object manipulation. Standard imitation learning policies such as A

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Plan, Don't Pose: Long Composite Motion Generation with Text-Aligned BFM

arXiv:2605.29906v1 Announce Type: new Abstract: Text-to-motion (T2M) generation has broad applications in character animation, virtual avatars, and human-robot interaction. Existing methods typically

Position: Stop Chasing the C-index when Evaluating Survival Analysis Models

arXiv:2506.02075v2 Announce Type: replace-cross Abstract: The current state of evaluation in survival analysis is plagued by the persistent use of evaluation metrics in ways that are misaligned with t

Practitioner Beliefs and Behaviors in AI-Enhanced Education: DOT Framework Survey Evidence

arXiv:2605.29041v1 Announce Type: new Abstract: This study reports findings from a cross-sectional survey (n = 72) of higher education practitioners examining beliefs, behaviors, and institutional con

PRO-CUA: Process-Reward Optimization for Computer Use Agents

arXiv:2605.29119v1 Announce Type: new Abstract: Computer use agents (CUAs) have shown strong potential for automating complex digital workflows, yet their training remains constrained by costly live e

Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation

arXiv:2310.14161v2 Announce Type: replace Abstract: Machine learning has been successfully applied to improve the efficiency of Mixed-Integer Linear Programming (MILP) solvers. However, the learning-b

Provably Secure Agent Guardrail

arXiv:2605.29251v1 Announce Type: new Abstract: As large language models transition from bounded generative engines to agents with expansive execution privileges, AI going out of control precipitates

Quantifying and Optimizing Simplicity via Polynomial Representations

arXiv:2605.29823v1 Announce Type: new Abstract: Deep networks often exhibit a preference for 'simple' solutions, and such a simplicity bias is widely believed to play a key role in generalization. Yet

Quantum-Enhanced Adversarial Robustness in Artificial Intelligence

arXiv:2605.28899v1 Announce Type: cross Abstract: Artificial Intelligence has achieved remarkable success across diverse application domains. However, its vulnerability to adversarial attacks poses si

quick, name a prominent company that achieved a major win via tokenmaxxing!

quick, name a prominent company that achieved a major win via tokenmaxxing! I've yet to see, or hear of a company that is winning against its competition, because said company is spending more on AI t

Quotient DAGs for Off-Policy Evaluation:Forward-Flow Importance Sampling and Exact Slate Propensities

arXiv:2605.29500v1 Announce Type: cross Abstract: Off-policy evaluation estimates how a target policy would perform using data collected by a different behavior policy, which is crucial when online te

Real-Time Retargeting Using Controllability Boundary for Chandrayaan-3 Lunar Landing

arXiv:2605.29412v1 Announce Type: cross Abstract: This paper presents the real-time retargeting guidance policy developed for the Chandrayaan-3 lunar landing mission. The baseline guidance generates a

Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers

arXiv:2601.22139v2 Announce Type: replace-cross Abstract: Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain funda

ReasonLight: A Multimodal Foundation Model-Enhanced Reinforcement Learning Framework for Zero-Shot Traffic Signal Control

arXiv:2605.29425v1 Announce Type: new Abstract: Reinforcement learning (RL) has shown promise in traffic signal control (TSC). However, its reliance on predefined states limits responsiveness to obser

Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents

arXiv:2605.29447v1 Announce Type: cross Abstract: While GUI agents have advanced rapidly, they often lack the robustness to recover from their own errors, hindering real-world deployment. To bridge th

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Recurrent Structural Policy Gradient for Partially Observable Mean Field Games

arXiv:2602.20141v2 Announce Type: replace Abstract: Mean Field Games (MFGs) provide a principled framework for modelling interactions in large population systems. However, algorithmic progress has bee

Reinforcing Few-step Generators via Reward-Tilted Distribution Matching

arXiv:2605.26108v2 Announce Type: replace Abstract: Recent advances in few-step diffusion distillation have enabled efficient image generation, yet aligning these models with human preferences remains

Replicable Simulation-Based Robot Validation through Provenance

arXiv:2605.29973v1 Announce Type: new Abstract: Robot behavior is often validated through simulation-based testing, yet the replicability of such campaigns depends critically on transparent documentat

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Representation Alignment Rests on Linear Structure

arXiv:2605.28870v1 Announce Type: cross Abstract: We investigate the Platonic Representation Hypothesis (PRH) through a tripartite statistical framework of representations: signal, bias, and noise. {1

Representation Signatures and Risk-Feedback Alignment in LLM Trading Agents

arXiv:2605.28850v1 Announce Type: new Abstract: We study behavioral alignment and representation dynamics of large language model (LLM) agents in financial decision environments. Using TradeArena, an

Resolution as a Direction: Vector-Panning Feature Alignment for Cross-Resolution Re-Identification

arXiv:2510.00936v2 Announce Type: replace Abstract: Cross-resolution person re-identification (CR-ReID) remains challenging in practical surveillance, where camera quality and capture distance lead to

Resolving Endpoint Underfitting in Diffusion Bridges via Noise Alignment

arXiv:2605.28962v1 Announce Type: new Abstract: Diffusion bridge models offer a powerful framework for connecting two data distributions, such as in image restoration and translation. Many existing me

REST3D: Reconstructing Physically Stable 3D Scenes from a Single Image

arXiv:2605.30338v1 Announce Type: new Abstract: Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applic

Review Arcade: On the Human Alignment and Gameability of LLM Reviews

arXiv:2605.28897v1 Announce Type: new Abstract: LLM-generated reviews for scientific papers are gaining considerable traction and are even being officially piloted by major conferences. We have to ass