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Beyond Extrapolation: Knowledge Utilization Paradigm with Bidirectional Inspiration for Time Series Forecasting

arXiv:2605.19249v1 Announce Type: new Abstract: Time-series forecasting is critical in various scenarios, such as energy, transportation, and public health. However, most existing forecasters rely pri

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Beyond Isotropy in JEPAs: Hamiltonian Geometry and Symplectic Prediction

DGX agent

arXiv:2605.20107v1 Announce Type: cross Abstract: JEPAs often regularize one-view embeddings toward an isotropic Gaussian, implicitly baking Euclidean symmetry into the representation. We show that th

safetyarxiv-cs-ai

20 May 2026

Beyond Mode Collapse: Distribution Matching for Diverse Reasoning

arXiv:2605.19461v1 Announce Type: new Abstract: On-policy reinforcement learning methods like GRPO suffer from mode collapse: they exhibit reduced solution diversity, concentrating probability mass on

Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection

arXiv:2605.19532v1 Announce Type: new Abstract: Text-to-image diffusion models can synthesize high-quality images, yet the outcome is notoriously sensitive to the random seed: different initial seeds

Brain alignment of reasoning and action representations from vision-language and action models during naturalistic gameplay

arXiv:2605.19352v1 Announce Type: cross Abstract: Understanding how humans and artificial intelligence systems predict and plan by interacting with their environment is a fundamental challenge at the

Can Large Language Models Revolutionize Survey Research? Experiments with Disaster Preparedness Responses

arXiv:2605.19229v1 Announce Type: new Abstract: Survey research faces mounting structural challenges: declining response rates, sample bias, block-wise missingness among at-risk respondents, and AI-as

CEER: Compliant End-Effector and Root Control as a Unified Interface for Hierarchical Humanoid Loco-Manipulation

arXiv:2605.19981v1 Announce Type: new Abstract: Humanoid robots have achieved impressive locomotion performance, yet contact-rich and long-horizon manipulation remains a major bottleneck. Manipulation

safetyarxiv-cs-ro

Certifiable Alignment of GNSS and Local Frames via Lagrangian Duality

arXiv:2512.20931v2 Announce Type: replace Abstract: Estimating the absolute orientation of a local system relative to a global navigation satellite system (GNSS) reference often suffers from local min

safetyarxiv-cs-ro

Chessformer: A Unified Architecture for Chess Modeling

arXiv:2605.19091v1 Announce Type: new Abstract: Chess has long served as a canonical testbed for artificial intelligence, but modeling approaches for its central tasks have diverged. Maximizing playin

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

arXiv:2507.15698v2 Announce Type: replace-cross Abstract: Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially fo

Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings

arXiv:2605.19374v1 Announce Type: cross Abstract: Vision-language alignment using chest X-rays and radiology reports has emerged as an advanced paradigm for zero-shot classification and grounding of c

Context-dependent manifold learning: A neuromodulated constrained autoencoder approach

arXiv:2603.11673v2 Announce Type: replace Abstract: Many physical systems exhibit a low-dimensional structure that varies with external parameters: link lengths in a robot, forcing constants in a flui

ContextFlow: Hierarchical Task-State Alignment for Long-Horizon Embodied Agents

arXiv:2605.19314v1 Announce Type: cross Abstract: Long-horizon embodied agents increasingly delegate navigation, search, approach, and manipulation to specialist executors. As these executors become s

CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning

arXiv:2605.20075v1 Announce Type: cross Abstract: Chain-of-thought (CoT) is a standard approach for eliciting reasoning capabilities from large language models (LLMs). However, the common CoT paradigm

CriterAlign: Criterion-Centric Rationale Alignment for Code Preference Judging

arXiv:2605.19665v1 Announce Type: cross Abstract: Pairwise human preference prediction is central to evaluating code-generation systems, where quality often depends on task-specific trade-offs beyond

Cross-modal Consistency Guidance for Robust Emotion Control in Auto-Regressive TTS Models

arXiv:2510.13293v3 Announce Type: replace Abstract: While Text-to-Speech (TTS) systems enable emotional control via natural-language instructions, expressiveness, naturalness, and speech quality degra

D-CLING: Prior-Preserving Depth-Conditioned Fine-Tuning for Navigation Foundation Models

arXiv:2605.19690v1 Announce Type: new Abstract: Navigation Foundation Models (NFMs) trained on large cross-embodied datasets have demonstrated powerful generalizability in various scenarios. Adopting

safetyarxiv-cs-ro

Data-driven Acceleration of MPC with Guarantees

arXiv:2511.13588v2 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) is a powerful framework for optimal control but can be too slow for low-latency applications. We present a data

DEFLECT: Delay-Robust Execution via Flow-matching Likelihood-Estimated Counterfactual Tuning for VLA Policies

arXiv:2605.19294v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies are typically deployed with asynchronous inference: the robot executes a previously predicted action chunk while

Dimensional Balance Improves Large Scale Spatiotemporal Prediction Performance

arXiv:2605.18793v1 Announce Type: cross Abstract: Accurate spatiotemporal pattern analysis is critical in fields such as urban traffic, meteorology, and public health monitoring. However, existing met

Directed Acyclic Graph Convolutional Networks

arXiv:2506.12218v2 Announce Type: replace-cross Abstract: Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architec

Domain-Adaptive Communication-Rate Optimization for Sim-to-Real Humanoid-Robot Wireless XR Teleoperation

arXiv:2605.19293v1 Announce Type: cross Abstract: Wireless extended reality (XR) teleoperation provides embodied interaction capability for collecting humanoid robot demonstrations, but the large-scal

Don't Let Bandit Feedback Pull Continual LLM-Recommender Updates Off Target

arXiv:2605.18899v1 Announce Type: cross Abstract: Generative LLM-based recommenders (LLM-Rec) require continual post-deployment updates, yet deployment logs provide only policy-shaped contextual bandi

Dual-Gated Epistemic Time-Dilation: Autonomous Compute Modulation in Asynchronous MARL

arXiv:2603.23722v2 Announce Type: replace-cross Abstract: While Multi-Agent Reinforcement Learning (MARL) algorithms achieve unprecedented successes across complex continuous domains, their standard d

DynaSTy: A Framework for SpatioTemporal Node Attribute Prediction in Dynamic Graphs

arXiv:2601.05391v2 Announce Type: replace Abstract: Accurate multistep forecasting of node-level attributes on dynamic graphs is critical for applications ranging from financial trust networks to biol

DynaTok: Temporally Adaptive and Positional Bias-Aware Token Compression for Video-LLMs

arXiv:2605.19322v1 Announce Type: new Abstract: Recent advances in Video Large Language Models (Video-LLMs) have greatly expanded multimodal reasoning capabilities. However, the massive number of visu

Efficient Transferable Optimal Transport via Min-Sliced Transport Plans

arXiv:2511.19741v3 Announce Type: replace Abstract: Optimal Transport (OT) offers a powerful framework for finding correspondences between distributions and addressing matching and alignment problems

Exact Linear Attention

arXiv:2605.18848v1 Announce Type: cross Abstract: This paper introduces Exact Linear Attention (ELA), a mechanism that achieves linear computational complexity for Transformer attention by leveraging

Extreme Self-Preference in Language Models

arXiv:2509.26464v2 Announce Type: replace Abstract: Self-preference is a fundamental feature of biological organisms. Since large language models (LLMs) lack sentience, they might be expected to avoid

Feature-Space Smoothing: Certified Robustness of Deep Representations

arXiv:2601.16200v3 Announce Type: replace-cross Abstract: Modern deep learning models exhibit strong capabilities across diverse applications, yet remain vulnerable to malicious inputs that induce err

Formal Skill: Programmable Runtime Skills for Efficient and Accurate LLM Agents

arXiv:2605.19604v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly act inside real workspaces, where tools and skills determine whether model reasoning becomes reliable act

GAE Falls Short in Imperfect-Information Self-Play Reinforcement Learning

arXiv:2605.19235v1 Announce Type: new Abstract: Competitive multi-agent reinforcement learning in imperfect-information games requires agents to act under partial observability and against adversarial

Generative-Evaluative Agreement: A Necessary Validity Criterion for LLM-Enabled Adaptive Assessment

arXiv:2605.19529v1 Announce Type: new Abstract: When the same LLM generates assessment items, simulates student responses, and scores them, the validation loop is self-referential. We introduce Genera

HeadRank: Decoding-Free Passage Reranking via Preference-Aligned Attention Heads

arXiv:2604.17237v2 Announce Type: replace-cross Abstract: Decoding-free reranking methods that read relevance signals directly from LLM attention weights offer significant latency advantages over auto

HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling

arXiv:2510.00054v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding tasks. However, their performance on high-resol

HOI-PAGE: Zero-Shot Human-Object Interaction Generation with Part Affordance Guidance

arXiv:2506.07209v2 Announce Type: replace-cross Abstract: We present HOI-PAGE, a new approach that prioritizes part-level affordance reasoning to generate high-fidelity 4D human-object interactions (H

How Do Document Parsers Break? Auditing Structural Vulnerability in Document Intelligence

arXiv:2605.19309v1 Announce Type: new Abstract: Document Layout Analysis (DLA) pipelines provide structured page representations for retrieval-augmented generation, long-document question answering, a

How does longer temporal context enhance multimodal narrative video processing in the brain?

arXiv:2602.07570v2 Announce Type: replace-cross Abstract: Understanding how humans and artificial intelligence systems process complex narrative videos is a fundamental challenge at the intersection o

How Does Overparameterization Affect Machine Unlearning of Deep Neural Networks?

arXiv:2503.08633v2 Announce Type: replace Abstract: Machine unlearning is the task of updating a trained model to forget specific training data without retraining from scratch. In this paper, we inves

Implicit Bias of Mirror Flow in Homogeneous Neural Networks: Sparse and Dense Feature Learning

arXiv:2605.19458v1 Announce Type: new Abstract: We study the max-margin solutions reached by mirror flow in deep neural networks with homogeneous activation functions. Extending classical results on g

Increasing Missingness to Reduce Bias: Richardson-SGD with Missing Data

arXiv:2605.19641v1 Announce Type: cross Abstract: Stochastic gradient methods are central to modern large-scale learning, but their use with incomplete covariates remains delicate since imputation sch

Interoceptive Divergence in Aesthetic Evaluation and Implications for Human-AI Alignment

arXiv:2605.18759v1 Announce Type: cross Abstract: Artificial intelligence (AI), exemplified by large language models (LLMs), is rapidly approaching and in some cases surpassing human performance acros

Inverse Design of Metasurface based Absorbers using Physics Guided Conditional Diffusion Models

arXiv:2605.19611v1 Announce Type: new Abstract: Inverse design of metasurfaces for specific electromagnetic responses requires generating geometries that satisfy stringent spectral constraints while m

LambdaPO: A Lambda Style Policy Optimization for Reasoning Language Models

arXiv:2605.19416v1 Announce Type: new Abstract: Group Relative Policy Optimization(GRPO) has become a cornerstone of modern reinforcement learning alignment, prized for its efficacy in foregoing an ex

Learning ORDER-Aware Multimodal Representations for Composite Materials Design

arXiv:2602.02513v2 Announce Type: replace Abstract: Artificial intelligence has shown remarkable success in materials discovery and property prediction, particularly for crystalline and polymer system

Learning with Foresight: Enhancing Neural Routing Policy via Multi-Node Lookahead Prediction

arXiv:2605.19975v1 Announce Type: cross Abstract: Neural policies have shown promise in solving vehicle routing problems due to their reduced reliance on handcrafted heuristics. However, current train

Low-Compute Watermark Removal via Dual-Domain Natural Projection

arXiv:2510.07538v2 Announce Type: replace Abstract: Effective removal of semantic watermarks requires balancing three competing objectives: high removal success, low perceptual distortion, and low com

Measuring Stereotype and Deviation Biases in Large Language Models

arXiv:2508.06649v3 Announce Type: replace Abstract: Large language models (LLMs) are widely applied across diverse domains, raising concerns about their limitations and potential risks. In this study,