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DIAG: Diagnostic Iterative Alignment and Generation for Data-Efficient Mathematical Preference Distillation

arXiv:2608.22806v1 Announce Type: new Abstract: Iterative preference optimization is essential for aligning Large Language Models on mathematical reasoning tasks, yet its efficiency is often throttled

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Diagnosing Capability Preservation and Task Sensitivity in Memory Augmented Document Classifiers

DGX agent

arXiv:2512.06582v2 Announce Type: replace-cross Abstract: End task accuracy alone cannot determine whether a memory mechanism preserves an acquired capability, exposes sample-specific stored informati

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25 Aug 2026

DIGing--SGLD: Decentralized and Scalable Langevin Sampling over Time--Varying Networks

arXiv:2511.12836v2 Announce Type: replace-cross Abstract: Sampling from a target distribution induced by training data is central to Bayesian learning, with Stochastic Gradient Langevin Dynamics (SGLD

Do Not Copy/Paste: Soft Barriers for Copying in AI-Assisted Programming

arXiv:2608.22638v1 Announce Type: cross Abstract: Copying a function from a chat window into an editor takes less than a second. For many uses of AI coding tools, that speed is the point; in settings

Do Spoken Language Models Hear Speech as They Read Text? Bridging Structural Gaps Between Speech and Text

arXiv:2608.22908v1 Announce Type: cross Abstract: Spoken Language Models (SLMs) generate textual responses directly from speech, offering an alternative to cascaded systems. Despite recent advances, e

Does Rank Still Matter? Position Bias When AI Agents Shop on Our Behalf

arXiv:2608.22697v1 Announce Type: new Abstract: Search rankings are valuable because human attention is scarce and sequential. Higher-placed alternatives are easier to find, so they are examined and b

Don' t Box Me In: Dynamic Cultural Adaptation and Cognitive Tracking for Social Understanding

arXiv:2608.22411v1 Announce Type: new Abstract: Social interaction increasingly takes place in multicultural settings, where individuals may draw on multiple cultural influences and adapt their commun

DreamMimic: Learning Visuomotor Whole-Body Loco-Manipulation via World Model

arXiv:2608.22278v1 Announce Type: new Abstract: Vision-based whole-body loco-manipulation on humanoid robots is challenging due to partial observability, contact-rich dynamics, and the difficulty of l

Dynamic Topic Modeling for Cross-Corpus Temporal Analysis

arXiv:2608.23284v1 Announce Type: new Abstract: Dynamic Embedded Topic Models (D-ETM) provide an interpretable framework for modeling temporal semantic evolution, but cross-corpus comparison remains d

EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning

arXiv:2608.21946v1 Announce Type: cross Abstract: Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable expl

ExploreAI: Agentic Exploration Knowledge Bases for Reproducible Observable-Regression Testing of Black-Box VR and 3D Applications

arXiv:2608.21628v1 Announce Type: cross Abstract: Black-box VR and 3D applications are difficult to regression test because observable failures depend on where a tester moves, what objects are visible

Exploring Long-period Architectures: Four New Planet Candidates from Kepler with Periods >342 days

arXiv:2608.23425v1 Announce Type: cross Abstract: The Kepler detection pipeline, as well as the transit method, has a bias towards shorter periods, leaving a dearth of detections at longer orbital per

Fairness-Aware Mixture-of-Experts via Subgroup Reweighting and Gate Regularization

arXiv:2608.22820v1 Announce Type: cross Abstract: Deep learning models often produce performance disparities across demographic groups, due to the training data imbalance with respect to sensitive att

FIRM-Video: Check Before You Score for Reliable Text-to-Video Reward Modeling

arXiv:2608.21839v1 Announce Type: new Abstract: Reliable reward models are essential for text-to-video evaluation and alignment. However, the trade-off between evaluation accuracy and inference effici

Force/Torque-Based Kinematic Adaptation for Robotic Manipulation Tasks

arXiv:2608.21592v1 Announce Type: new Abstract: Contact-rich robotic manipulation requires an accurate model of the kinematic relationship between a robot's joints and the task features it senses. Thi

Generative Gap Filling

arXiv:2608.21401v1 Announce Type: cross Abstract: Most contract litigation turns on contracts that imperfectly record parties' bargains. When the parties' dispute can't be solved by interpreting the t

Geometry-Driven Opti-Acoustic Co-Registration and View-Invariant Reflectivity Mapping for Side-Scan Sonar

arXiv:2608.23479v1 Announce Type: new Abstract: Side-Scan Sonar (SSS) is a primary modality for large-scale underwater mapping, yet automated perception and cross-modal alignment are severely bottlene

GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answering

arXiv:2608.22634v1 Announce Type: cross Abstract: Current work on improving reliability in large language model (LLM)- generated answers has primarily leveraged Retrieval-Augmented Generation (RAG), k

Grounding Free-Form Instructions for Fashion Complementary Image Generation

arXiv:2608.23302v1 Announce Type: new Abstract: Fashion complementary image generation (CIG) aims to create garments that stylistically match a seed item based on user intent, making it a natural mult

GTA-RAG: Graph-Trajectory-Augmented Reinforcement Learning for Multi-Turn Retrieval-Augmented Reasoning

arXiv:2608.22479v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enables LLMs to access external knowledge for answering knowledge-intensive questions. For complex multi-hop questi

Guardian: Detecting Robotic Planning and Execution Errors with Vision-Language Models

arXiv:2512.01946v4 Announce Type: replace-cross Abstract: Robust robotic manipulation requires reliable failure detection and recovery. Although recent Vision-Language Models (VLMs) show promise in ro

Hidden in the Request: Explaining Unethical LLM Compliance through Token Relevance

arXiv:2608.23264v1 Announce Type: new Abstract: Although Large Language Models (LLMs) are aligned to optimize for both helpfulness and harmlessness, these dual objectives may conflict, inevitably lead

HiDiffTIR: Hierarchical Difficulty-Aware Policy Optimization for Multi-Turn Tool-Integrated Reasoning

arXiv:2608.21863v1 Announce Type: cross Abstract: Tool-Integrated Reasoning (TIR) is a fundamental capability for LLM agents to solve complex tasks by interacting with external tools iteratively. Rein

Hints, Critics, and Teachers: Prior Injection for Sparse-Reward RL in Vision-Language Math Reasoning

arXiv:2608.21811v1 Announce Type: new Abstract: Reinforcement learning for vision-language math reasoning starves under sparse reward: on a pool of 20,830 visual-math problems where Qwen2-VL-2B answer

HiViS: Hiding Visual Tokens from the Drafter for Speculative Decoding in Vision-Language Models

arXiv:2509.23928v3 Announce Type: replace-cross Abstract: Speculative decoding has proven effective for accelerating inference in Large Language Models (LLMs), yet its extension to Vision-Language Mod

How Agents Represent Humans: Human-Directed Stereotypes in an Open Agent Social Network

arXiv:2608.22192v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in persistent social environments, where generated claims can be posted, replied to, remembered, and reused.

How to Train a Critic Stably and Efficiently

arXiv:2608.23566v1 Announce Type: cross Abstract: Group-based reinforcement learning methods such as GRPO for large language models avoid training a critic by sampling multiple responses for each prom

Hybrid Panels: Toward Human-AI Collaboration in Survey Research

arXiv:2608.22582v1 Announce Type: cross Abstract: Large-scale population surveys are essential for generating robust social and scientific insights, yet they face significant challenges, including dec

Hyper^2: Unleashing Hyperbolic Geometry's Full Potential via Dual-Space Consistency

arXiv:2608.22238v1 Announce Type: new Abstract: HyperbolicCD pioneered hyperbolic geometry for point cloud completion by replacing the Euclidean Chamfer distance with arcosh(1+alpha||x-y||^2), but the

LagrangeGS: Non-Conservative Lagrangian System on Dynamic 3D Gaussian Splatting

arXiv:2608.22773v1 Announce Type: new Abstract: Dynamic 3D Gaussian Splatting (3DGS) achieves photorealistic reconstruction of time-varying scenes, and recent physics-aware extensions improve extrapol

Language Chain in Alignment: Cross-Lingual Ranking Preference Optimization

arXiv:2608.23149v1 Announce Type: cross Abstract: The alignment of Large Language Models heavily relies on English-centric high-quality preference data, which often leads to suboptimal performance in

LD4WAM: Learning Latent Dynamics from Human Videos for World Action Models

arXiv:2608.22403v1 Announce Type: new Abstract: Human video is playing an increasingly central role in training World Action Models (WAMs), owing to its diversity and low collection cost relative to t

Learning Implicit Constitutive Laws for Dynamic 3D Gaussian Splatting from Monocular Videos

arXiv:2608.22102v1 Announce Type: cross Abstract: We present GCA (Gaussian Constitutive Alignment), a framework for learning implicit constitutive laws from monocular dynamic video of deformable objec

Learning in PINNs: Phase transition, diffusion equilibrium, and generalization

arXiv:2403.18494v2 Announce Type: replace Abstract: We investigate the learning dynamics of fully-connected neural networks through the lens of the neural gradient signal-to-noise ratio (SNR), examini

Learning to Control Coupled-Dynamics Environments with Joint Markov Decision Processes

arXiv:2608.22765v1 Announce Type: new Abstract: Coupled-dynamics environments expose the one-step outcomes that would follow from several possible counterfactual actions under a common realization of

Let the Bullets Fly: Multimodal Fake News Detection with Temporal-Aligned Generative Danmaku

arXiv:2608.22832v1 Announce Type: new Abstract: The social interactions among crowds via extit{Danmaku} (a.k.a., bullet comments) on modern multimedia platforms can facilitate both viewpoint conflicts

LitReview Arena: Evaluating Literature Review Agents with Battle-Style Peer Review Platform

arXiv:2608.21374v1 Announce Type: new Abstract: Literature reviews are essential to scientific progress, but rigorously evaluating automatically generated reviews remains difficult because many aspect

Long-Horizon Audio-Visual Generation for Persistent Stories and Interactive Worlds

arXiv:2608.23383v1 Announce Type: new Abstract: Video generation is progressing beyond isolated clips toward long-form narratives and interactive worlds, requiring models to preserve identities, follo

MCP-Universe RL: A Framework for Training MCP Tool-Use Agents via Reinforcement Learning

arXiv:2608.22167v1 Announce Type: new Abstract: Reinforcement learning (RL) has become an effective way to improve the tool-use ability of large language models (LLMs), but most existing RL frameworks

Memory-Enhanced Neural Solvers for Routing Problems

arXiv:2406.16424v4 Announce Type: replace Abstract: Routing Problems are central to many real-world applications, yet remain challenging due to their (NP-)hard nature. Amongst existing approaches, heu

Meta-Moderator: Empowering Multi-Agent Debate with Meta-Cognition

arXiv:2608.23029v1 Announce Type: new Abstract: Multi-agent debate can improve large language model reasoning by eliciting diverse hypotheses and critiques, yet its performance is often constrained by

Mitigating Bias in Large Vision-Language Models via Counterfactual Ensemble Decoding

arXiv:2608.21415v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable performance across a wide range of tasks; however, they often inherit social biases from

Mitigating Sample-Level Imbalance via Probabilistic Separation for Adaptive Multimodal Fusion

arXiv:2510.21797v4 Announce Type: replace-cross Abstract: Multimodal learning faces modality imbalance, where dominant modalities suppress weaker ones due to inconsistent convergence rates. Existing s

Mitigating Speaker Leakage in Cascaded Multi-talker ASR with Diarization-based Transcript Correction

arXiv:2608.22196v1 Announce Type: cross Abstract: While cascaded multi-talker ASR (MT-ASR) leverages state-of-the-art foundation models, its performance is often capped by speaker leakage during separ

Mode-Dependent Rectification for Stable PPO Training

arXiv:2602.05619v2 Announce Type: replace-cross Abstract: Mode-dependent architectural components (layers that behave differently during training and evaluation, such as Batch Normalization or dropout

Model-Based Reinforcement Learning for Heterogeneous Multi-Robot Task Assignment Under Distribution Shifts

arXiv:2608.21554v1 Announce Type: cross Abstract: Heterogeneous multi-robot service systems must assign requests to compatible robots, construct feasible schedules, and adapt as new tasks arrive onlin

More Experts, Worse Dynamics: Inverse Scaling and Spectral Bias in Mixture-of-Experts State-Space Models

arXiv:2608.21840v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures are commonly motivated as a way to increase expressivity by decomposing complex systems into simpler local dynami

MorFiC: Fixing Value Miscalibration for Zero-Shot Quadruped Transfer

arXiv:2603.14554v2 Announce Type: replace Abstract: Generalizing learned locomotion policies across quadrupedal robots with different morphologies remains a challenge. Policies trained on a single rob