Search: “models”

arXiv:2610.12099v1 Announce Type: new Abstract: World action models (WAMs) aim to answer a coupled physical question: given a task instruction, what motion should the robot execute, and how will that

applicationsarxiv-cs-ro

9 Oct 2026

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VICO: Visual Environments Co-Evolving for Vision-Language Model Reasoning

DGX agent

arXiv:2610.10782v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard recipe for post-training vision-language models (VLMs), but it typically a

researcharxiv-cs-ai

9 Oct 2026

Why LLM Agents Favor Their Group: Stakes, Observed Norms, and Reputation

arXiv:2610.11008v1 Announce Type: cross Abstract: Language-model agents favor their own group because they have watched their members favor each other. The group label alone does little once the decis

9 Oct 2026

Counterfactual Route Optimization for Gaussian Head Avatar Modeling

arXiv:2610.09791v1 Announce Type: new Abstract: Head avatar modeling requires jointly optimizing multiple objectives with different dominant effects on geometry, appearance, and cross-view consistency

researcharxiv-cs-cv

EngramEdit: Decoupled Knowledge Updates in LLMs through Conditional Memory

model-releasesarxiv-cs-cl

arXiv:2610.10533v1 Announce Type: new Abstract: Conditional memory architectures such as DeepSeek Engram use input n-grams to look up learned embeddings, expanding the capacity of large language model

From Retrieval to Customer Context: Evaluating Frontier-Model Systems for Voice-of-Customer Analysis

arXiv:2610.09375v1 Announce Type: new Abstract: Organizations increasingly use frontier language models to analyze customer feedback, but answer quality also depends on how that feedback is organized

agentsarxiv-cs-lg

HeiCo-FOCUS: A Clinically Grounded Dataset for Long-Context Video Understanding

arXiv:2610.10156v1 Announce Type: new Abstract: Recent advances in Vision-Language Models (VLMs) have led to rapid progress in video understanding across a wide range of benchmark tasks. However, exis

Kernel Autoresearch for Open-Ended Model Discovery

arXiv:2610.10394v1 Announce Type: new Abstract: Kernels encode the inductive bias of a wide range of machine learning models, yet automated kernel design faces a fundamental dilemma. A fixed grammar o

safetyarxiv-cs-lg

Route-Verify-Vote: Procedure-Conditioned Self-Consistency for Mixed-Domain Reasoning

model-releasesarxiv-cs-cl

arXiv:2610.08814v1 Announce Type: cross Abstract: Compositional generalization remains challenging when language models must combine familiar reasoning operations in unfamiliar ways. The Scenario-Base

AIM: Adaptive Interaction Modeling Networks for Real-to-Sim Soft-Body Simulation

arXiv:2610.07116v1 Announce Type: new Abstract: Deformable-object manipulation is essential for robotic tasks such as folding laundry and handling food, where robots must control shape changes as well

local-aiarxiv-cs-ro

Benchmarking Label-Revealed Online Updates for EEG BCI Decoding

arXiv:2610.07420v1 Announce Type: new Abstract: Electroencephalography (EEG) signals drift over time, which can cause static brain-computer interface (BCI) models to degrade in practice. We present a

Decoupling What from Where: How Should a Small GUI Grounding Model Receive the Action Type?

arXiv:2610.07444v1 Announce Type: cross Abstract: A GUI agent decides which action to take and where to take it; we ask how a small grounding model should receive the action type. Fine-tuning Qwen2-VL

agentsarxiv-cs-cv

Foundation Model-Aided Multi-Agent Reinforcement Learning for Wireless Random Access Network Optimization

arXiv:2610.07550v1 Announce Type: cross Abstract: Random access (RA) is one of the most foundational medium access control (MAC) layer scheduling schemes for handling unpredictable data traffic from m

local-aiarxiv-cs-ai

GAMEGO: Training Game-Dev Agents with Synthetic Trajectories Anchored in Real-World Assets

arXiv:2610.06910v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities in web front-end execution, with browser-based game generation

Generalizable Dense Reward for Long-Horizon Robotic Tasks

arXiv:2604.00055v2 Announce Type: replace-cross Abstract: Existing robotic foundation policies are trained primarily via large-scale imitation learning. While such models demonstrate strong capabiliti

MS-ECG-FM: Towards a More Universal Electrocardiogram Foundation Model for Health Monitoring using Multi-source Contrastive Learning

arXiv:2610.07662v1 Announce Type: new Abstract: Electrocardiography (ECG) records the electrical activity of the heart, aiding diagnosis by detecting abnormalities in cardiac function. ECG foundation

safetyarxiv-cs-lg

Multimodal Knowledge Distillation for Gastric Adenocarcinoma Classification from Whole-Slide Images

arXiv:2610.07913v1 Announce Type: cross Abstract: Gastric adenocarcinoma (GA) is a leading cause of cancer-related mortality worldwide, and accurate histopathological subtype classification from whole

PlaySuite: A Large-Scale Benchmark for Interactive Visual Intelligence

arXiv:2610.07127v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models yield strong performance on static perception and reasoning benchmarks, yet such evaluations largely o

Which and When to Admit: Gradient Admission for Data-Centric Small Language Model Finetuning

arXiv:2610.07553v1 Announce Type: cross Abstract: LoRA fine-tuning adapts small language models (SLMs) to heterogeneous instruction data within a low-rank update subspace, making it vulnerable to thre

researcharxiv-cs-ai

AgroGround: Multi-Granularity Grounded Recognition in Agriculture

arXiv:2610.04425v1 Announce Type: new Abstract: Agricultural visual models are typically evaluated for either recognition or localization, but reliable diagnosis requires identifying what is present a

Attention Tax, Handoff Tax: A Stylised Model of When Multi-Agent LLM Systems Help

arXiv:2610.06069v1 Announce Type: cross Abstract: Recent work on multi-agent LLM systems reaches sharply different conclusions: some results show that a single agent with the same information and comp

agentsarxiv-cs-lg

BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents

arXiv:2610.06748v1 Announce Type: cross Abstract: In decentralized consumer-to-consumer (C2C) marketplaces, people list goods, negotiate with strangers, and rate one another, so trust rests on reputat

Budget-Constrained Fault-Tolerant Mutual Visibility for Autonomous Robots under the Mobility Fault Model

arXiv:2610.04402v1 Announce Type: cross Abstract: We investigate the mutual visibility problem for a swarm of nge3 autonomous mobile robots under the budget-constrained mobility fault model. The robot

agentsarxiv-cs-ro

EchoDino: A pediatric foundation model for transferable echocardiographic analysis across the lifespan

arXiv:2610.05603v1 Announce Type: new Abstract: Echocardiography is the most widely used cardiac imaging modality, yet interpretation demands integrating visual evidence across global anatomy, localiz

local-aiarxiv-cs-cv

Greedy Local Learning for Language Model Pretraining: Gaps and Objective Design

arXiv:2610.04867v1 Announce Type: new Abstract: Greedy block-wise local learning splits a network into gradient-isolated blocks trained by local auxiliary losses, deleting the backward pass between bl

local-aiarxiv-cs-lg

How RL Reshapes LLM Reasoning: Transferability, Coverage, and Scaling Laws

arXiv:2610.04158v1 Announce Type: new Abstract: Recent studies on reinforcement learning (RL) report seemingly conflicting evidence about large language model (LLM) reasoning. Training on mathematics

Machine learning modeling of hit-into-play probability and quantification of pitch sequence effects

arXiv:2606.17345v2 Announce Type: replace Abstract: Although pitch sequencing is a central topic in baseball analytics, previous studies have primarily focused on improving predictive performance for

researcharxiv-cs-lg

Tutorials

Prism: Dynamic Sparse Attention for Native 2K Joint Video-Audio Generation Model Training

arXiv:2610.05416v1 Announce Type: new Abstract: Natively training joint video-audio generation models at higher resolutions empowers them to learn richer visual details and sharper motion dynamics. Ho

tutorialsarxiv-cs-cv

Reachability-Guided Sequential Quadratic Programming-Guarded Model Predictive Path Integral for Safe Nonlinear Predictive Control

arXiv:2610.04406v1 Announce Type: new Abstract: Safe robot control often requires combining long-horizon performance optimization with hard state and input constraints, but existing approaches tend to

local-aiarxiv-cs-ro

Reinforcement Learning on the Discrete Composition Channel of a Crystal Generator: Validated Gains and Reward Hacking

arXiv:2610.03880v1 Announce Type: new Abstract: Inverse materials design is a long-standing goal of computational materials discovery. Generative models for crystalline materials are typically trained

Rotated, but How Far? Diagnosing and Improving Object-Rotation Reasoning in VLMs

arXiv:2610.05715v1 Announce Type: new Abstract: Vision-language models (VLMs) can detect that an object has rotated across views, but cannot reliably tell by how much. We introduce OR-Bench, a fine-gr

Hardware

Static Bootstrap Placement for Encrypted Language Model Decoding

arXiv:2610.04912v1 Announce Type: cross Abstract: Language models increasingly serve prompts that carry private data, and secure inference under homomorphic encryption lets a client outsource the comp

hardwarearxiv-cs-lg

Applications

Virtual model control for compliant reaching under uncertainties

arXiv:2610.05695v1 Announce Type: new Abstract: Virtual Model Control (VMC) is an approach to design a controller for force-controlled robots in complex uncertain environments. While this method was p

applicationsarxiv-cs-ro

What Will Post-Training Fix? Per-Problem Gains Are Shared Across Independent RL Runs, and Existing Checkpoints Predict Them Better Than A Priori Signals

arXiv:2610.04978v1 Announce Type: new Abstract: Data selection, curricula and the evaluation of post-training recipes all assume that we can tell, before training, which problems a model will improve

ConvoDrift: A Multi-Turn Conversational Dataset for Modeling Stylistic Tone Evolution

arXiv:2610.02873v1 Announce Type: cross Abstract: The evolution of linguistic style in conversations is an underexplored issue in NLP. Most style-control datasets focus on sentences or assume a static

safetyarxiv-cs-ai

CriticHack: Evaluating Visual Rewards Under Robot Policy Optimization

arXiv:2610.02527v1 Announce Type: cross Abstract: Learned visual reward models are increasingly used to optimize robot policies, yet a reward model can score an execution that acts on the wrong object

Tutorials

Misinformation Without Triggers: From Factual Answers to Downstream Decisions

arXiv:2610.02886v1 Announce Type: cross Abstract: Language models learn from web documents, some of them false, and false content can reach a model's answer to a factual question and the summaries and

tutorialsarxiv-cs-ai

Psi-Resilience: Model-Free Feature Importance from 1D Topological Signals

arXiv:2610.02299v1 Announce Type: cross Abstract: We introduce Psi-Resilience, a model-free feature importance method that derives explanations directly from the data itself via 1D topological signals

researcharxiv-cs-ai

Tutorials

Toward Omni Multimodal Graph Foundation Model: A Topology-Driven Binding Approach

arXiv:2610.02881v1 Announce Type: new Abstract: Multimodal graph foundation models (MGFMs) seek to learn generalizable representations from large-scale graphs with heterogeneous node modalities. Howev

tutorialsarxiv-cs-lg

Agent Evaluation Reliability: More Tasks Won't (Always) Fix An Agent Leaderboard

arXiv:2610.00651v1 Announce Type: new Abstract: Agent evaluations are increasingly used to compare LLMs and inform deployment decisions, yet ranks can reflect not only the model but also the effects o

CrossGMN: Graph Metanetworks for Cross-Architecture Weight-Space Transformations

arXiv:2610.01649v1 Announce Type: new Abstract: Weight-space networks operate directly on parameters of other neural networks, enabling tasks such as predicting model properties, editing trained model

FAER: Auditable Utility-Aligned Trajectory Replay for Language Model Post-Training

arXiv:2610.00385v1 Announce Type: cross Abstract: Replay selectors often rank cached trajectories by format feedback, confidence, freshness, or response length, although cache-level correctness and do

safetyarxiv-cs-ai

Applications

NarrativeFlow: Flow-Based Vision-Language-Action Model Using Robot Velocity Fields

arXiv:2610.00981v1 Announce Type: cross Abstract: We focus on language-conditioned flow-based manipulation, where robot flows (robot velocity fields) serve as embodiment-agnostic, motion-centric repre

applicationsarxiv-cs-cv

PG-SFT: Balancing Capability Acquisition and Retention in Offline Agent Fine-Tuning

arXiv:2610.00949v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) on offline agent trajectories is the standard approach for training specialized tool-using agents, but forcing models to im

Quantifying Diversity of Thought: A Predictive Law of Weighted LLM Ensemble Lift

arXiv:2607.17384v3 Announce Type: replace Abstract: This paper provides an experimentally verified formal law for calculating the uplift that diversity of thought provides in Large Language Model (LLM

Selection-Based Structured Reasoning: Toward Efficient Multimodal Search Agents

arXiv:2610.01892v1 Announce Type: cross Abstract: Multimodal agents commonly generate free-form reasoning before each action. For small models, limited model capacity can result in lengthy reasoning t

researcharxiv-cs-ai

UrbanVLA: A Vision-Language-Action Model for Urban Micromobility

arXiv:2510.23576v2 Announce Type: replace-cross Abstract: Urban micromobility applications, such as delivery robots, demand reliable navigation across large-scale urban environments while following lo

safetyarxiv-cs-ai

Beyond Text: LLM-Based Dimensional Emotion Evaluation in Multimodal Dialogue

arXiv:2609.39072v1 Announce Type: cross Abstract: Emotion recognition in conversation has been widely studied, but applying Large Language Models (LLMs) to continuous dimensional emotion evaluation in