Search: “framework”

MoF: Preference-Aware Mixture Modeling for Black-Box LLM Personalization

arXiv:2610.08330v1 Announce Type: new Abstract: Proprietary Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet aligning their outputs with diverse

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

DGX agent

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

model-releasesarxiv-cs-ai

7 Oct 2026

Applications

Navigating Route Latent Space for Synthesizable Molecular Design

arXiv:2610.07560v1 Announce Type: new Abstract: Goal-directed molecular design has advanced rapidly, yet a substantial proportion of designed molecules remain difficult to synthesize in practice, limi

applicationsarxiv-cs-ai

Navigation with RF Cues: Embodied Perception Action under Multipath Uncertainty

model-releasesarxiv-cs-ro

arXiv:2610.08105v1 Announce Type: new Abstract: Smart factory inspection requires robots to reach connected equipment without a prior map or known target coordinates. Radio frequency (RF) signals from

Neural Algorithmic Reasoning for Graph Saddle Point Problems

arXiv:2610.07255v1 Announce Type: new Abstract: Neural algorithmic reasoning, or aligning a neural network with an algorithmic paradigm, has emerged as an approach to solving polynomial-time-solvable

safetyarxiv-cs-lg

Nonlocal Hamiltonian Dynamics on Sparse Levy Graphs: Spectral Analysis and Multimodal Sampling

arXiv:2610.06904v1 Announce Type: cross Abstract: We develop a sparse graph method for transporting probability mass toward multimodal target distributions through damped nonlocal Hamiltonian dynamics

Nord-Parl-TTS: Finnish and Swedish TTS Dataset from Parliament Speech

arXiv:2509.17988v2 Announce Type: cross Abstract: Text-to-speech (TTS) development is limited by scarcity of high-quality, publicly available speech data for most languages outside a few high-resource

researcharxiv-cs-cl

One for All, All for One: Coordinated Multi-Agent Diffusion Steering via Stochastic Optimal Control

arXiv:2610.08595v1 Announce Type: cross Abstract: Deep generative models often produce structured outputs composed of interacting components. Modelling these outputs with a single model requires learn

agentsarxiv-cs-ai

OOPMAS: Object-Oriented Multi-Agent Systems for Query-Level Workflow Generation

arXiv:2610.07787v1 Announce Type: new Abstract: Multi-agent systems (MAS) powered by large language models have shown strong performance across code generation, mathematical reasoning, and question an

Optimization Encoders: Rethinking Second-Order Meta-Learning for Neural Fields

arXiv:2610.08075v1 Announce Type: cross Abstract: Conditional neural fields represent signals continuously, but their effectiveness depends on how the conditional latent representations are inferred f

Pareto-Optimal Entropy-Regularized Trajectory Optimization

arXiv:2610.08532v1 Announce Type: new Abstract: Trajectory optimization (TO) under nonlinear dynamics, actuation limits and collision avoidance constraints is a fundamental problem in robotics, albeit

researcharxiv-cs-ro

Partially Observable Zero-shot coordination by Predicting Intention of Partner

arXiv:2610.08142v1 Announce Type: new Abstract: Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving existing methods with ambiguous par

agentsarxiv-cs-ai

PEARS: Physical-Prior-Guided Efficient Adaptation via Failure Reasoning and Diffusion Steering for Tactile Manipulation

arXiv:2610.08784v1 Announce Type: new Abstract: Pretrained robotic policies can suffer substantial performance degradation under out-of-distribution (OOD) conditions encountered during deployment, mot

safetyarxiv-cs-ro

Performative Prediction with Selective Labels

arXiv:2610.08272v1 Announce Type: new Abstract: Many social applications of machine learning exhibit performative effects: population behavior changes in response to deployed models. Performative pred

safetyarxiv-cs-lg

Applications

PhoneBot: A Low-Cost Open Humanoid Robot Platform Reusing Smartphones

arXiv:2610.08737v1 Announce Type: new Abstract: The adoption of humanoid robots in education and research remains limited by high hardware costs, complex sensing systems, and substantial computational

applicationsarxiv-cs-ro

PhysTacGen: Physics-Aware Visual-Tactile Sensor Image Generation

arXiv:2610.08068v1 Announce Type: new Abstract: Realistic physical interaction is a cornerstone of embodied intelligence, yet collecting paired visual--tactile data remains costly. Visual-to-tactile s

PIE-PS: Photometric Stereo from Physical Irradiance Event Streams

arXiv:2610.08188v1 Announce Type: new Abstract: Event cameras record asynchronous log-image-irradiance changes with microsecond latency and high dynamic range. These properties are useful for photomet

researcharxiv-cs-cv

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

POLAR: Ontology-Guided Risk Prevention for Tool-Calling LLM Agents

arXiv:2610.08082v1 Announce Type: new Abstract: LLM tool-use agents operate in dynamic environments where many actions carry operational risk. However, most safety mechanisms react only after errors m

safetyarxiv-cs-ai

Porting LIBERO to MuJoCo Warp: 130 robot manipulation tasks on one $700 AMD GPU

model-releasesr-localllama

LIBERO is a robot manipulation benchmark: 130 tasks across five suites (spatial, object, goal, scene10, scene90), each with human demos and a language goal. It is the standard testbed for language-con

Preserving Unstable Modes Through Inverse Dynamics in JEPA World Models

arXiv:2610.07540v1 Announce Type: new Abstract: Robotic systems often exhibit unstable modes, along which small perturbations and disturbances can cause unbounded growth unless corrected through feedb

Principles that Guide, Actions that Inform: Agent Evolution via Knowledge Abstraction

arXiv:2610.06964v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experi

Probabilistic Counterfactual Inference for Discrete Outcomes in Gaussian-Process Causal Models

arXiv:2610.08689v1 Announce Type: new Abstract: Counterfactual inference in Gaussian-process structural causal models (GP-SCMs) has been developed primarily for continuous endogenous variables, limiti

PRUE: A Practical Recipe for Field Boundary Segmentation at Scale

model-releasesarxiv-cs-cv

arXiv:2603.27101v2 Announce Type: replace Abstract: Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field ma

Applications

QiYao-I: A Manifold Based Foundation Model for Irregular Multivariate Time Series Forecasting

arXiv:2610.06936v1 Announce Type: new Abstract: Irregular multivariate time series forecasting is a challenging yet important problem in real-world applications, where observations are often irregular

applicationsarxiv-cs-lg

Qubit-centric Transformer for Surface Code Decoding

arXiv:2510.11593v3 Announce Type: replace-cross Abstract: For reliable large-scale quantum computation, quantum error correction (QEC) is essential to protect logical information distributed across mu

researcharxiv-cs-ai

RA-MoWE: Workflow-Affinity Embeddings for Query Clustering and Agentic Workflow Generation

arXiv:2610.07851v1 Announce Type: new Abstract: Agentic workflows enable large language models (LLMs) to solve complex tasks by coordinating reasoning, tool use, and verification. However, a workflow

agentsarxiv-cs-ai

RACE-FPP: A Robust AI-assisted Characterisation Enhancement for Fringe Projection Profilometry

arXiv:2610.08213v1 Announce Type: new Abstract: Fringe Projection Profilometry (FPP) requires precise system characterisation to achieve reliable three-dimensional (3D) reconstructions; however, chara

researcharxiv-cs-cv

Rationale-Guided Policy Optimization: Learning to Reason with Adaptive Rationale Scaffolding

arXiv:2610.07342v1 Announce Type: new Abstract: On-policy reinforcement learning has become a central paradigm for improving the reasoning abilities of large language models. However, its effectivenes

safetyarxiv-cs-ai

RBMatch: Dual-Level Class Rebalancing for Semi-Supervised Building Footprint Extraction

arXiv:2610.07698v1 Announce Type: new Abstract: Accurate building footprint extraction from high-resolution remote sensing imagery is essential for urban planning, disaster response, and environmental

ReDex: Repairing Sim-to-Real Dexterous Policies by Finger-Level Compliant Interaction

arXiv:2610.07525v1 Announce Type: new Abstract: Dexterous manipulation policies trained in simulation often fail to transfer to the real world because of errors in contact timing and force regulation.

safetyarxiv-cs-ro

RefRoute: Decoupling Conditioning Cost from References via Compact Residual Conditioning and Spatial Routing

model-releasesarxiv-cs-cv

arXiv:2610.07720v1 Announce Type: new Abstract: Multi-reference image generation requires preserving the appearance of multiple subjects while composing them into a coherent scene. However, existing d

Reinforcement Learning with Segment Reward Feedback under Linear Function Approximation

arXiv:2610.08271v1 Announce Type: new Abstract: Classical reinforcement learning (RL) assumes that a reward is observed for every visited state-action pair. However, in real-world applications such as

agentsarxiv-cs-lg

RELACE: retrospective likelihood-based action credit estimation for long-horizon language agents

arXiv:2610.07349v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) avoids a separate critic by estimating advantages from rollout groups. For multi-turn agents, however, traje

local-aiarxiv-cs-ai

REPA-G: Test-Time Conditioning with Representation-Aligned Visual Features

arXiv:2602.03753v2 Announce Type: replace Abstract: While representation alignment with self-supervised models has been shown to improve diffusion model training, its potential for enhancing inference

Retrieval Is Not Enough: Refreshing Memory for Frozen Time-Series Forecasters

arXiv:2610.07834v1 Announce Type: new Abstract: Retrieval-augmented time-series forecasting uses the continuations of historical segments similar to the current context as references for a forecaster.

safetyarxiv-cs-lg

Revisiting Numerical Forecasting Models for Language-Based Trajectory Prediction

arXiv:2610.07954v1 Announce Type: new Abstract: Language-based trajectory predictors represent coordinates as discrete tokens and learn auxiliary tasks such as destination and group reasoning. This fo

Risk-Sensitive Crowd Navigation with Adaptive Ellipsoidal Conformal Prediction

arXiv:2610.07474v1 Announce Type: new Abstract: Safe crowd navigation under distribution shift requires uncertainty representations that capture structured human-motion prediction errors and safety ob

safetyarxiv-cs-ro

RIWANav: Recursive World-Action Models with Self-Improvement for Urban Navigation

arXiv:2610.08640v1 Announce Type: new Abstract: Long-horizon urban navigation requires sequential local decisions whose errors can compound over time. Imitation learning (IL) rarely learns from failur

local-aiarxiv-cs-ro

Robust Importance Sampling for Rare Events via Constrained Gaussian Mixtures

arXiv:2610.07485v1 Announce Type: new Abstract: We study estimating rare-event probabilities I = P(g(mathbf{X}) > gamma) with mathbf{X} sim N(oldsymbol{mu}, oldsymbol{Sigma}) and general g : R^d o R.

Tutorials

ROMA: LLM System for Real-World Object-Centric Multi-Sensory Active Perception

arXiv:2610.06955v1 Announce Type: cross Abstract: Humans inherently understand the physical world through an active process. When sensory evidence is insufficient to infer physical properties, we natu

tutorialsarxiv-cs-cv

RSJEV: Discriminative Remote Sensing Scene Classification with Multimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2610.08539v1 Announce Type: new Abstract: Remote sensing scene classification is a fundamental task in Earth observation and geospatial analysis. Existing approaches mainly follow three paradigm

SAGE: Semantic Anchor-Guided Evolution for Grounded Medical QA Data Synthesis

arXiv:2610.08093v1 Announce Type: cross Abstract: Developing reliable models for clinical tasks, such as Medical Question Answering (QA), is severely constrained by the limited availability of high-qu

local-aiarxiv-cs-ai

Sample-Optimal Estimation of the Frechet Inception Distance

arXiv:2610.07114v1 Announce Type: cross Abstract: The Frechet Inception Distance (FID) is widely used to evaluate generative models, but its empirical plug-in estimator suffers from finite-sample bias

SchemaFill: Efficient LLM Tool Calling via Slot-Parallel Speculative Decoding

arXiv:2610.07086v1 Announce Type: cross Abstract: LLM agents interact with external systems by generating structured tool calls. Given a user request, conversational context, and a catalog of tool sch

researcharxiv-cs-ai

ScienceClaw: Benchmarking Continual Self-Evolution of AI-for-Science Agents Across the Natural and Social Sciences

arXiv:2610.08691v1 Announce Type: new Abstract: Large language model agents are accelerating scientific automation, yet verified executions rarely become persistent program-level improvements, and exi

Selective Critique for Cost-Aware LLM Agents in Long-Horizon Decision Making

arXiv:2610.07335v1 Announce Type: cross Abstract: Improving the reliability of large language model (LLM) agents in long-horizon decision-making remains a key challenge. When deployed as autonomous ag

local-aiarxiv-cs-ai

Self-Referenced Social Preferences: Cooperation without Observing Others Rewards

arXiv:2610.07881v1 Announce Type: new Abstract: Social preferences can promote cooperation in multi-agent reinforcement learning, but existing approaches often require agents to observe the rewards of

safetyarxiv-cs-ai