Search: “models”

DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction

arXiv:2610.22130v1 Announce Type: new Abstract: Key-value (KV) cache management has become a critical bottleneck for scaling Large Language Models (LLMs) to long-context scenarios due to linear memory

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Encoded but Exposed: Language Embeddings can Reveal More Than They Should in Recommender Systems

DGX agent

arXiv:2610.21713v1 Announce Type: cross Abstract: Language embeddings are increasingly used in recommenders to represent item content, but their privacy risks remain poorly understood. We study whethe

safetyarxiv-cs-ai

16 Oct 2026

Evaluating Inquiry Learning in LLM-Based Agents: Hypothesizing, Reasoning, and Exploration

arXiv:2610.21604v1 Announce Type: new Abstract: Scientific inquiry involves iterative cycles of exploration, hypothesis generation, and reasoning over observations to uncover relationships in complex

Failure Is the Mother of Success: Recovering Supervision with Grounding Hindsight

arXiv:2610.21018v1 Announce Type: new Abstract: When every rollout for a problem fails, GRPO receives neither a successful exemplar nor a nonzero group-relative advantage, so it learns nothing from ex

GraphACM: Graph-based Action Consistency Measurement for Uncertainty Quantification in LLM Agents

arXiv:2610.22031v1 Announce Type: new Abstract: Behavioral consistency across repeated executions provides an informative signal for assessing the reliability of large language model (LLM) agents. How

Applications

Hierarchical Graph Convolutional Network Approach for Detecting Low-Quality Documents

arXiv:2610.21350v1 Announce Type: new Abstract: Consistency within a document is a crucial feature indicative of its quality. Recently, within the vast amount of information produced across various me

applicationsarxiv-cs-ai

How Much Physics Can Vision Learn from Audio? Probing and Distilling Damping Structure

arXiv:2610.22221v1 Announce Type: new Abstract: Physical understanding is crucial for decision making, yet vision models struggle to infer properties such as damping that govern how materials behave.

tutorialsarxiv-cs-cv

Hybrid Generative-Tagging Decoding for Efficient Product Attribute-Value Extraction

arXiv:2610.21329v1 Announce Type: new Abstract: Attribute-value extraction is important for building high-quality product catalogs in e-commerce. Existing systems either rely on generative or tagging

KNOU-Flood: Advancing global streamflow forecasting with lead-aware probabilistic machine learning

arXiv:2610.20640v1 Announce Type: new Abstract: Global streamflow forecasting supports flood preparedness, yet data-driven models trained on reanalysis lose skill when driven by operational forecasts,

KnowGPO: Knowledge-Grouped Policy Optimization for Search Agents

arXiv:2610.22331v1 Announce Type: new Abstract: Deep search agents solve knowledge-intensive tasks through long-horizon, multi-turn interactions, where assigning credit to individual search decisions

L2G-SR: Learning to Guide LLM-based Symbolic Regression

arXiv:2610.20685v1 Announce Type: new Abstract: Symbolic regression searches for an equation that explains observed data. Numerical error is commonly used to guide the search, but it alone can favor a

tutorialsarxiv-cs-ai

Learn Only Where You Can't Compute: Structured Corrections to Gaussian Process Posteriors

arXiv:2610.21977v1 Announce Type: new Abstract: Physics-informed Gaussian processes (GPs) provide a principled framework for scientific inference by expressing uncertainty over empirical measurements,

tutorialsarxiv-cs-lg

Learning at the Right Pace: Adaptive Data Scheduling Improves LLM Reinforcement Learning

arXiv:2606.22305v2 Announce Type: replace Abstract: Large Language Models (LLMs) achieve remarkable reasoning capabilities through reinforcement learning (RL) post-training. However, existing RL post-

safetyarxiv-cs-cl

Learning Changes the World and Then What Was Learned has Changed: Training and Deploying Neural Networks in the Control Loop

arXiv:2610.22084v1 Announce Type: cross Abstract: Neural networks offer critical adaptability for controlling complex systems where nominal modeling proves intractable. However, when offline-trained n

safetyarxiv-cs-lg

Local Ai

Learning Self-Orchestration in Decentralized Agent Swarms

arXiv:2610.22322v1 Announce Type: cross Abstract: The capabilities of an agent swarm depend on both its individual members and how they coordinate. Yet existing multi-agent systems often train agents

local-aiarxiv-cs-ai

Learning to Steer LLM Agents and Multi-Agent Systems

arXiv:2610.22316v1 Announce Type: cross Abstract: Large language model (LLM)-based agents and multi-agent systems increasingly tackle complex tasks through long-horizon tool use and inter-agent collab

Let's Ask Gauss: Improved One-Run Privacy Auditing

arXiv:2606.12733v3 Announce Type: replace Abstract: Privacy auditing provides an important safeguard by estimating the actual information leaked by a model, thus ensuring that theoretical privacy guar

Local Ai

LICOA: Learning Instruction-Conditioned Optical Actions for Mobile Spatial Augmented Reality

arXiv:2610.21282v1 Announce Type: cross Abstract: Spatial augmented reality (SAR) augments physical environments with projected content, but most systems assume that the projector pose, target region,

local-aiarxiv-cs-cv

LLM-as-an-Investigator: Evidence-First Agentic Reasoning for Robust Interactive Problem Diagnosis

arXiv:2606.13220v2 Announce Type: replace Abstract: Large language models (LLMs) are used for technical troubleshooting, where problem descriptions are often incomplete and multiple causes can explain

LLM-Based Weak Annotation for Cybersecurity Tweet Classification: A Teacher-Student Framework

arXiv:2610.21254v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) relies on the timely identification of emerging threats, enabling organizations and security analysts to support situati

Machine-learning-based neutrino-event generation constrained by experimental measurements

arXiv:2610.20870v1 Announce Type: cross Abstract: We present a generative surrogate for charged-current (nu_mu)-nucleus scattering that can be calibrated to measured differential cross sections withou

ManiFusion: Unlocking the High-Throughput Generation via Superposition in Manifold Space

arXiv:2610.21433v1 Announce Type: new Abstract: Diffusion models achieve high-quality image generation but remain computationally expensive due to iterative denoising across many timesteps. Existing a

tutorialsarxiv-cs-cv

MARS - A foundational map auto-regressor

arXiv:2610.20843v1 Announce Type: new Abstract: Map generation tasks feature extensive non-structural vectorized data (e.g., points, polylines, and polygons) and thus pose significant challenges to co

Multi-SFT: Permissively-Licensed Multilingual Instruction-Following

arXiv:2610.22086v1 Announce Type: cross Abstract: Supervised fine-tuning datasets remain overwhelmingly English-centric and commercially restricted, as their content is frequently generated by proprie

Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation

arXiv:2610.20881v1 Announce Type: new Abstract: While foundation models and vision transformers (ViTs) have redefined visual representations, current active learning (AL) strategies for these backbone

Planning Commitment of LLM under Partial Observability

arXiv:2610.21108v1 Announce Type: new Abstract: LLM-based planning agents commit to plans of different lengths before interacting with a partially observable environment. Some aggressively commit to a

PRISM: PRIvileged Sibling-guided Multi-Agent Topology Design

arXiv:2610.20628v1 Announce Type: new Abstract: Multi-agent systems (MAS) based on large language models (LLMs) have become a powerful way to address complex problems, and their effectiveness depends

agentsarxiv-cs-cl

PROBE: Learning to Audit Policy Compliance in Tool-Using LLM Agents

arXiv:2610.22124v1 Announce Type: new Abstract: Modern agentic systems extend language models with external tools, enabling them to complete complex tasks through multi-turn interactions. As these age

Ranking and Partitioning of Attention Heads for Sparse and Continual Reinforcement Learning Fine-tuning

arXiv:2610.21336v1 Announce Type: cross Abstract: We study sparse and continual reinforcement learning fine-tuning of language models through attention-head ranking and partitioning. For sparse learni

Robust Covariance Estimation for Entry-wise Contaminated and Partially Observed Data via Expectation Maximization Algorithm

arXiv:2610.21709v1 Announce Type: cross Abstract: Robust covariance estimation under entry-wise contamination and missing data is challenging in various signal processing applications. Under the Stude

Rubric Judgments Lack Uncertainty: Conformal Weighting for LLM Evaluation

arXiv:2610.21214v1 Announce Type: new Abstract: Rubric-based evaluation is widely used to assess large language model (LLM) outputs by decomposing quality into multiple criteria and assigning each a b

SATOR: Backpropagation-Free 3D Test-Time Adaptation via Sample-Adaptive Token Routing

arXiv:2610.21367v1 Announce Type: new Abstract: Test-time adaptation (TTA) mitigates the performance degradation of source-pretrained models on unlabeled test data under distribution shifts. Recent ba

Scene Reconstruction Using Ubiquitous Wireless Signals via Diffusion Posterior Inference Over physics-Grounded Representations

arXiv:2610.22120v1 Announce Type: new Abstract: Knowing the layout of the physical world matters for many applications, yet the sensors we rely on for it (e.g., cameras and LiDAR) can fail in darkness

Scientific feedback reveals productive regimes beyond training conventions

arXiv:2512.15756v2 Announce Type: replace-cross Abstract: Human-imposed design conventions can restrict the alternatives represented in scientific training data and shape the search preferences learne

Seeing Both the Forest and the Trees: Reusing Holistic 3D Priors for Part-Decomposed Generation

arXiv:2610.21850v1 Announce Type: new Abstract: Generating 3D assets with explicit parts requires two properties at once: geometric detail inside each part and structural coherence across the whole ob

Applications

Self-Guided LLM Reasoning for Error Diagnosis in Vehicle Routing Problems

arXiv:2610.21393v1 Announce Type: new Abstract: Vehicle Routing Problems (VRPs) are fundamental to many real-world applications. Recent advances in large language models (LLMs) have spurred progress i

applicationsarxiv-cs-ai

SoftCache: Adaptive Step Size Caching for Diffusion Transformers

arXiv:2610.22369v1 Announce Type: new Abstract: Diffusion and flow models generate a sample over iterative steps, each a full pass through a large network, and that pass dominates generation cost. Tra

Applications

SPEAR: Selective Preference Elicitation with Adaptive Rewards for VLM-Guided Robotic Manipulation

arXiv:2610.21621v1 Announce Type: new Abstract: Recent Vision-Language Models (VLMs) enable automated preference labeling for robotic manipulation, yet their deployment remains impractical since each

applicationsarxiv-cs-ro

Spectral-Spatial Interpretation

arXiv:2610.21114v1 Announce Type: cross Abstract: Post-hoc image explanations usually show where a model looks using spatial heatmaps or indicate which channels matter using global channel scores. The

safetyarxiv-cs-cv

T-GADE: Thermodynamical Generative-AI-Driven Evolution of LLM Artifacts

arXiv:2609.12286v2 Announce Type: replace Abstract: Introducing large language models (LLMs) into evolutionary computation enables semantic generation of candidates, but the classical problem of maint

The Right Byte First: How UTF-16 Helps Multilingual Boundary Prediction

arXiv:2610.22071v1 Announce Type: new Abstract: Many hierarchical byte-level language models group bytes into patches using a learned boundary predictor whose view of the next codepoint depends on enc

Towards Better Aligned LLM Judges for Radiology Report Evaluation across Modalities and Anatomies

arXiv:2604.03376v2 Announce Type: replace Abstract: Current work on radiology report evaluation has focused primarily on LLM-based metrics for chest X-rays (CXR), leaving open whether such approaches

V-SHARE: Provable Convergence Guarantees for Advantage-based Algorithms

arXiv:2610.21448v1 Announce Type: cross Abstract: In reinforcement learning, advantage-based value-learning methods, unlike standard Q-learning, share information across actions by decomposing the act

When Judges Agree and Are Wrong: Consistency-Accuracy Dissociation as a Blind Spot for Label-Free Evaluation

arXiv:2610.21128v1 Announce Type: cross Abstract: Label-free evaluation methods, such as self-consistency filtering, majority-vote aggregation, and agreement-based reliability scoring, rely on an impl

Which Tokens to Merge? Diffusion Dynamics for Efficient Image Generation

arXiv:2610.22370v1 Announce Type: new Abstract: Token merging has emerged as an effective training-free strategy for accelerating diffusion models by reducing redundant token computation while minimiz

A Diagnostic Study of World-Space Human Recovery Under High Camera Dynamics

arXiv:2610.19729v1 Announce Type: new Abstract: Monocular world-space human recovery methods excel on current benchmarks, but these rarely include fast camera motion. We introduce the K-Pop stress tes

15 Oct 2026

A Global View of How LLMs Value Human Time

arXiv:2610.18515v2 Announce Type: cross Abstract: Large language models (LLMs) increasingly act as personal assistants; however, little is known about how they capture national-level preferences on a

15 Oct 2026

Local Ai

Accelerating VLA Inference with Perturbation Informed Execution