All entries

DPPM: Dual-Path Parametric Memory for Personalized Language Models

arXiv:2610.11776v1 Announce Type: new Abstract: Long-term personalization requires language models to use interaction history to track users' preferences across sessions. Parametric memory encodes thi

researcharxiv-cs-cl

Source

Human DGX agent

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DreamTrue: Action-Faithful Robot World Model with Counterfactual Post-Training

DGX agent

arXiv:2610.12468v1 Announce Type: cross Abstract: We present DreamTrue, a multi-view, cross-embodiment robot world model for action-faithful and physically plausible video prediction. Training such a

safetyarxiv-cs-cv

9 Oct 2026

Agents

DuplexAgent-RSI: Recursive Harness Improvement for Full-Duplex Voice Agent Collaboration

arXiv:2610.11299v1 Announce Type: new Abstract: Voice agents are converging on a collaboration pattern: a full-duplex interaction model stays on the live channel as the entry to the conversation, whil

agentsarxiv-cs-ai

DVD: Dynamic Vector Decoding for Efficient MLLM-based Perception

arXiv:2610.12266v1 Announce Type: cross Abstract: Multimodal large language models have made remarkable progress in bridging vision and language, facilitating various perception tasks essential for hu

local-aiarxiv-cs-ai

DVLA-RL++: Dual-Level Vision-Language Alignment with Reinforcement Learning Gating for Few-Shot Learning

arXiv:2610.12095v1 Announce Type: new Abstract: Few-shot learning aims to recognize novel categories from limited labeled examples. Recent studies incorporate textual semantics to compensate for limit

Dynamic Free-Rider Detection in Cross-Silo Federated Learning via Simulated Attack Patterns

arXiv:2604.04611v3 Announce Type: replace Abstract: Federated learning (FL) enables multiple clients to collaboratively train a global model by aggregating local updates without sharing private data.

local-aiarxiv-cs-lg

Dynamics as Code: On Model Compression via Dynamic System

arXiv:2610.11115v1 Announce Type: new Abstract: The escalating size of pretrained neural networks has rendered model compression a prerequisite for deployment under stringent memory and compute constr

researcharxiv-cs-lg

DynaTE: Accelerating Diffusion LLMs via Dynamic Token Execution

arXiv:2610.11284v1 Announce Type: cross Abstract: Diffusion-based LLMs (dLLMs) have recently emerged as a promising alternative to autoregressive (AR) LLMs by enabling bidirectional parallel refinemen

Early Signatures of Memorization in Diffusion Models via Basin Geometry and Cyclic Denoising

arXiv:2610.11670v1 Announce Type: new Abstract: Diffusion models generalize early in training and later reproduce individual training samples. Standard tests detect memorization only once one-shot gen

Easy to anticipate, hard to compute: boundary dependence finds the computed outputs that entropy patching misses

arXiv:2610.11790v1 Announce Type: new Abstract: Byte-level language models such as the Byte Latent Transformer (BLT) group bytes into patches and run their large global model once per patch. BLT start

researcharxiv-cs-cl

EchoDiST: Self-distillation-based joint learning for diffusion-conditioned echocardiographic myocardial motion estimation

arXiv:2610.11431v1 Announce Type: new Abstract: Motion estimation in echocardiography is essential for quantitative assessment of cardiac function and myocardial mechanics, but remains challenging due

Ecology of AI Agents: Collaboration Creates a Population Threshold for Takeoff

arXiv:2610.12436v1 Announce Type: new Abstract: AI agents can now conduct real-world cyberattacks, scale up capabilities with the number of agents, and collectively pursue misaligned goals to obtain r

Efficient and Generalizable Archetypal Analysis for Discrete Data

arXiv:2610.12035v1 Announce Type: cross Abstract: Archetypal Analysis (AA) represents observations as convex combinations of extremal data-driven profiles, yielding interpretable low-dimensional descr

local-aiarxiv-cs-lg

Efficient Multi-Granularity Knowledge Transfer for Radiology Report Generation

arXiv:2610.11303v1 Announce Type: new Abstract: Radiology report generation can automatically generate clinical descriptions from X-ray images, thereby significantly improving the efficiency of radiol

researcharxiv-cs-cv

Efficient quadratic entropy with distance sketches

arXiv:2610.11976v1 Announce Type: cross Abstract: We detail scalable methods for approximating the quadratic entropy p^T d p for arbitrary distributions p and common distances d of negative type. We f

Efficient Reasoning via Constrained Optimization in Latent Space

arXiv:2609.34181v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have shown remarkable reasoning capabilities, yet they still suffer from overthinking, generating redundant reasoning

EgoPhys: Estimating Peak Contact Force and Mechanical Work from Egocentric Manipulation Video

arXiv:2610.11347v1 Announce Type: new Abstract: Physically grounded manipulation of articulated objects requires understanding both the maximum forces encountered during contact and the work performed

researcharxiv-cs-cv

Applications

EgoVoice: Proactive Spoken Assistance from Egocentric Multimodal Streams

arXiv:2610.12248v1 Announce Type: new Abstract: Wearable augmented reality (AR) assistants are moving toward continuous real-world interaction, where they perceive the user's activity through first-pe

applicationsarxiv-cs-cl

Elucidating the Space of Enzymatic Reaction: A Unified Benchmark and Pretrained Model

arXiv:2610.11694v1 Announce Type: cross Abstract: Existing reaction models primarily learn molecular transformations, whereas enzy- matic reactions depend jointly on molecular structure and catalytic

Embedding-Bias in Conditional Independence Testing

arXiv:2610.11584v1 Announce Type: cross Abstract: To test conditional independence of X and Y given a text or an image Z, one conditions on an embedding psi(Z) in place of Z. The embedded test is vali

Embodied Turing Machines: Stateful Code for Robot Recursive Self-Improvement

arXiv:2610.12369v1 Announce Type: cross Abstract: Most robot policies keep a model in the control loop: a VLA maps observations to actions, and an Agent Harness, such as Agent-as-Policy or Harness VLA

Emergent Inverse-Depth Scaling From Nonlinearity In Attention

arXiv:2610.11063v1 Announce Type: cross Abstract: Scaling laws describe power-law improvements in model performance with dataset size and parameter count, yet their underlying mechanisms are not fully

Enabling Preference-driven Unlearning in Few-step Distilled Text-to-Image Diffusion Models

arXiv:2610.10859v1 Announce Type: new Abstract: Text-to-image diffusion models are increasingly distilled into few-step variants and being deployed to enable fast inference. However, their ability to

Enabling Quantum Natural Language Processing for Hindi Language

arXiv:2312.01221v2 Announce Type: replace Abstract: Quantum Natural Language Processing (QNLP) is taking huge leaps in solving the shortcomings of classical Natural Language Processing (NLP) technique

researcharxiv-cs-cl

Environmental Feedback Modeling Matters: Rethinking Feedback Treatment in Agentic Hindsight Self-Distillation

arXiv:2610.11384v1 Announce Type: new Abstract: Reinforcement learning is commonly used to train language agents in interactive environments, but cannot be directly applied when rewards are unavailabl

safetyarxiv-cs-ai

Epistemic Disturbance in the Graph Model for Conflict Resolution: State-Preserving Actions, Four-Valued Assessments, and the Distinction between Capability and Intention

arXiv:2610.11690v1 Announce Type: cross Abstract: In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing. The basic definit

Equal Path Cost, Unequal Output Effects: Understanding Perturbation Propagation in Diffusion Models

arXiv:2610.11380v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in generative modeling, with their sampling procedures routinely modified to control generation and im

Equilibrium Distribution for t-Distributed Stochastic Neighbor Embedding with Generalized Kernels

arXiv:2505.24311v3 Announce Type: replace-cross Abstract: We study the large-sample variational problem for t-distributed stochastic neighbor embedding with a class of input and output kernels. The in

Error-Propagation Modeling for Failure Attribution in LLM-Based Multi-Agent Systems

arXiv:2610.11600v1 Announce Type: new Abstract: LLM-based multi-agent systems (MASs) are increasingly used to solve complex tasks through coordinated reasoning, tool use, and interaction with external

Estimating great expectations under autoregressive language models with potentials

arXiv:2610.11399v1 Announce Type: new Abstract: Many applications of language models hinge not on individual samples but on the expectation of a test functional under the model. Estimating such expect

tutorialsarxiv-cs-ai

Evaluating Exact Output and Checkpoint-State Prediction in Real Programs

arXiv:2610.11889v1 Announce Type: cross Abstract: We present a benchmark for predicting final output and checkpoint state from source and input alone. It extends CRUXEval-style output prediction with

Evaluating Local Language Model Agents for Reproducible Data Engineering: An Empirical Software Engineering Study of Mobility Workflows

arXiv:2610.11482v1 Announce Type: cross Abstract: Context: Large language model (LLM) agents are increasingly used as software and data-engineering assistants, yet evidence about locally deployable op

Evaluating Rubric Generation with Interventional Transfer

arXiv:2610.10809v1 Announce Type: new Abstract: Instance-specific rubrics are common in AI benchmarks where reliable evaluation requires specific expert knowledge. This approach is difficult to scale,

Event-Centric Memory with Query-Aware Graph Augmentation for Long-Term Conversational Agents

arXiv:2610.11920v1 Announce Type: new Abstract: For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing pas

local-aiarxiv-cs-cl

Evi-VN: Hard Region Guided Virtual Node Evidence Injection for GNN-Based Fraud Detection

arXiv:2610.11665v1 Announce Type: new Abstract: Online platforms contain growing numbers of bots, deceptive reviewers, and scam accounts that imitate legitimate users. Such camouflage blurs graph neig

tutorialsarxiv-cs-lg

Evidence-Traceable Dynamic Interviewer Architecture for Expertise-Adaptive Qualitative Interviews Using Local LLMs

arXiv:2610.11651v1 Announce Type: new Abstract: Automated interviewers and conversational agents are increasingly used in research, recruitment, customer service, and education. However, many existing

local-aiarxiv-cs-ai

Agents

EvoAlloc: A Self-Evolving Resource Allocation Agent for Efficient Program Evolution

arXiv:2610.12086v1 Announce Type: new Abstract: LLM-based program evolution relies on evaluation feedback to guide the iterative search for high-performing programs. However, evaluation is often compu

agentsarxiv-cs-ai

EvoKnow: Continual Knowledge Evolution for AI-Generated Image Detection

arXiv:2610.11381v1 Announce Type: cross Abstract: AI-generated image detectors are commonly trained on fixed generator domains and become difficult to maintain as new generative models emerge. Continu

Agents

EvoSim: Learning to Model, Modeling to Learn

arXiv:2610.11344v1 Announce Type: new Abstract: Physics-based models connect scientific explanation with quantitative prediction. Constructing them requires selecting physical processes, defining stat

agentsarxiv-cs-ai

Exact SO(3)-Equivariant Isotropic Kernels for Rotation-Robust Neural Dynamics

arXiv:2610.10626v1 Announce Type: new Abstract: Neural surrogates for vector-valued partial differential equations can fit training data yet change their predictions when the same physical state is ex

Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology

arXiv:2610.12022v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external

Example-driven Parametrisations for Bayesian Shape Optimisation

arXiv:2610.11984v1 Announce Type: new Abstract: Bayesian optimisation is the natural tool for shape design when objectives are expensive and non-differentiable, but it needs a compact yet expressive p

tutorialsarxiv-cs-lg

ExecVLA: Following Fine-Grained Execution Constraints in Vision-Language-Action Models with Bi-Level Action Representation

arXiv:2603.17524v2 Announce Type: replace-cross Abstract: We study fine-grained execution-constraint following in vision-language-action (VLA) models. Given an invariant task goal, the policy must fol

safetyarxiv-cs-ai

Applications

Experience-Guided Initiation Search for Learned Skills in Skill Composition

arXiv:2610.11418v1 Announce Type: new Abstract: Deploying frozen learned skills, such as Vision-Language-Action (VLA) policies, in new environments requires identifying initiation configurations that

applicationsarxiv-cs-ro

Explaining the Saliency Map Sparsity of Adversarially-Trained Neural Networks

arXiv:2610.10666v1 Announce Type: new Abstract: Understanding why deep neural networks make a given prediction is of great importance for their safe deployment. In computer vision, saliency maps, whic

researcharxiv-cs-lg

Explanation Multiplicity in SHAP: Characterization and Assessment

arXiv:2601.12654v3 Announce Type: replace-cross Abstract: SHAP explanations are widely used in high-stakes settings to justify decisions, yet they can differ substantially across repeated runs, even w

Exploiting Gradients in Bayesian Inference of Expensive Simulators

arXiv:2610.12076v1 Announce Type: new Abstract: Simulators based on differential equations are ubiquitous in science and engineering. They are often used in simulation-based inference to evaluate the

tutorialsarxiv-cs-lg

Expression-Diverse References for Identity-Preserving Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.11023v1 Announce Type: new Abstract: Identity-preserving video generation aims to maintain a subject's identity while synthesizing realistic videos. Yet a single reference portrait captures