Search: “framework”

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

Local Ai

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SALTO: Solver-Anchored Lifted Transfer Operators for Nonlinear Event Inference

DGX agent

arXiv:2610.21049v1 Announce Type: new Abstract: Learned dynamical models can accurately predict trajectories while producing unreliable sensitivities when differentiated or transposed, limiting their

local-aiarxiv-cs-lg

16 Oct 2026

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

SCARCE: Emergent Institutions in Long-Horizon Multi-Agent Coding Systems

arXiv:2610.21029v1 Announce Type: cross Abstract: As autonomous agents become widely deployed, coordinating access to shared computing resources and services will become increasingly important. Recent

Second Maximum of a Gaussian Random Field and Exact (t-)Spacing test

arXiv:2406.18397v4 Announce Type: replace-cross Abstract: In this article, we introduce the novel concept of the second maximum of a Gaussian random field defined on a Riemannian manifold: Once the fi

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

Selection Is Not Learning: Choosing Model Futures

arXiv:2610.22029v1 Announce Type: cross Abstract: Self-evolving language models train on tasks they generate, so every round must decide which updated model the next round inherits. Current loops such

Shortcut Sensitivity in Agent-Safety Evaluations

arXiv:2610.22243v1 Announce Type: new Abstract: AI agents take actions through tools. Some actions are sensitive, so guards that supervise them must themselves be evaluated reliably. Yet the data used

SHRED: Self-Play for Heterogeneous Road-Users without Expert Demonstrations

arXiv:2610.20866v1 Announce Type: cross Abstract: Realistic traffic simulation and autonomous planning both depend on modeling interactions among heterogeneous road users whose dynamics, constraints,

SIEVE: Overcoming Topological Obstruction in Equivariant Self-Supervised Learning

arXiv:2610.21087v1 Announce Type: cross Abstract: We identify a theoretical incompatibility between 3D point cloud masked autoencoding and SE(3)-equivariant networks. We prove that standard masking tr

researcharxiv-cs-ai

Sim-to-Real Reinforcement Learning for Path-Safe Target Reaching in Robotic Harvesting of Hydroponic Lettuce

model-releasesarxiv-cs-ro

arXiv:2610.22337v1 Announce Type: new Abstract: Robotic harvesting requires precise manipulation to ensure accurate positioning of the end-effector, especially in a constraint workspace. This study in

SNOAR: Self-training with Noise filtering, Observation adding, and Remixing for Speech Denoising Without Clean References

arXiv:2610.20863v1 Announce Type: cross Abstract: Unsupervised speech denoising methods such as MixIT and noisy-target training can be trained directly on noisy recordings, avoiding the sim-to-real ga

Sparse Attention for Video Generation Acceleration via Growing Sparsity and Reduced Search

arXiv:2610.21129v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) dominate video generation but suffer from high inference cost due to the quadratic complexity of self-attention. Sparse at

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

Speculative Forcing for Efficient Autoregressive Video Generation

arXiv:2610.22347v1 Announce Type: new Abstract: Few-step autoregressive video generators enable streaming generation, yet they run every token through the final denoising step, regardless of how much

SSR: Structural Signal Retriever for Scalable Agent Discovery in LLM-Orchestrated Multi-Agent Systems

arXiv:2610.21113v1 Announce Type: cross Abstract: Large-scale multi-agent ecosystems require mechanisms for discovering suitable agents without exposing entire registries to a large language model (LL

Stabilizing the Modality Gap: Null-Space Projected Continual Learning for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2507.19839v2 Announce Type: replace-cross Abstract: The modality gap is intrinsic to multimodal alignment, where embeddings from different modalities remain partially separated in a shared repre

Stateful Testing for Deep Learning Compilers

arXiv:2610.22003v1 Announce Type: cross Abstract: Modern deep learning compilers compile models lazily and cache artifacts across invocations. Retained compiler state can make a later invocation incor

StepSafe: Learning Timely Intervention with Context-Aware Safety Reasoning

arXiv:2610.20960v1 Announce Type: new Abstract: Safety in agentic systems is inherently sequential: whether an action is safe depends on prior actions, tool outputs, information disclosures, and inter

StochLOB: Heavy-Tailed Score Matching for Robust Limit Order Book Trend Prediction

arXiv:2610.21081v1 Announce Type: new Abstract: Score-based diffusion methods usually perturb data with Brownian Gaussian noise, corresponding to a light-tailed forward stochastic differential equatio

Stop Training Against Soft Users: Mentalized Adversarial Self-Play for Proactive Dialogue

arXiv:2610.21156v1 Announce Type: new Abstract: Proactive dialogue agents must guide multi-turn interactions toward task goals while adapting to users whose intentions and attitudes evolve. Existing p

safetyarxiv-cs-cl

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

researcharxiv-cs-ai

TASTE: Task-Aware Out-of-Distribution Detection via Stein Operators

arXiv:2602.07640v2 Announce Type: replace Abstract: Out-of-distribution detection methods are often either data-centric, detecting deviations from the training input distribution irrespective of their

TEM: Temporal State Tracking Memory for Large Language Model Agents

arXiv:2610.21900v1 Announce Type: new Abstract: An agent's memory must remain useful as information changes across conversations. A new fact may replace an earlier value without making that value irre

agentsarxiv-cs-cl

The Dormant Spiking Neuron: A State-Driven Mechanism for Efficient Spiking Neural Networks

arXiv:2610.21748v1 Announce Type: new Abstract: Spiking neural networks (SNNs) offer a compelling pathway toward energy-efficient artificial intelligence, fundamentally anchored in presynaptic input-d

safetyarxiv-cs-cv

Towards Unbiased On-Policy Distillation for Block Diffusion Language Models

arXiv:2610.05373v2 Announce Type: replace Abstract: On-policy distillation (OPD) has emerged as an effective post-training paradigm for language models, with recent efforts extending it to block diffu

safetyarxiv-cs-cl

TRACE: Typed Reference-Aware Conversational Editing for Humanoid Motion Diffusion

arXiv:2610.21515v1 Announce Type: new Abstract: Language-conditioned humanoid motion generation enables users to create and refine robot movements through natural language. The central challenge is to

safetyarxiv-cs-ro

Applications

Trajectory-based Diffusion from One-shot Human Video for Generalizable Manipulation

arXiv:2610.21792v1 Announce Type: new Abstract: Imitation learning enables robots to perform complex tasks by leveraging human-collected demonstrations. However, most existing approaches require labor

applicationsarxiv-cs-ro

Translation Circuit Discovery and Targeted Optimization for Low-Resource Multilingual Translation

model-releasesarxiv-cs-cl

arXiv:2610.21456v1 Announce Type: new Abstract: Recent multilingual large language models achieve strong translation performance, yet the internal mechanisms responsible for low-resource multilingual

TS-WAM: Temporal Latent Actions and World-Action Coupling for Vision-Language Robot Control

arXiv:2610.21922v1 Announce Type: new Abstract: Many vision-language-action policies rely on action-labeled robot demonstrations and lack an explicit mechanism for predicting future visual states. The

safetyarxiv-cs-ro

Twice Upon a Time: Complementary Representations for Time-Series Reasoning

arXiv:2610.22327v1 Announce Type: cross Abstract: Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what inf

Hardware

UltraDiff: Transferring High-Fidelity Priors to Compressed Latent Spaces for High-Resolution Image Generation

arXiv:2610.21202v1 Announce Type: new Abstract: High-resolution synthesis with Latent Diffusion Models (LDMs) faces a fundamental trade-off between computational cost and generative fidelity. This tra

hardwarearxiv-cs-cv

UniFGVC: Universal Training-Free Few-Shot Fine-Grained Vision Classification via Attribute-Aware Multimodal Retrieval

arXiv:2508.04136v4 Announce Type: replace-cross Abstract: Few-shot fine-grained visual classification (FGVC) aims to discriminate between subtly different categories with very limited data. While Mult

VALCON: Benchmarking and Enhancing Value Consistency in Large Language Models via Dual-Role Variation

model-releasesarxiv-cs-cl

arXiv:2610.21304v1 Announce Type: new Abstract: Current value alignment evaluations for large language models (LLMs) heavily rely on output compliance, overlooking whether LLMs maintain value consiste

Value as Memory: Online Value-Guided Post-training for General Robot Policies

arXiv:2610.22368v1 Announce Type: new Abstract: Real-world post-training of generalist robot policies faces two challenges: partial observability makes action selection ambiguous, while offline post-t

safetyarxiv-cs-ro

Tutorials

VLA-Delta: Learning Physical State Transition for Vision-Language-Action Models

arXiv:2610.21306v1 Announce Type: new Abstract: Vision-language-action (VLA) models transfer semantic knowledge acquired through vision-language pretraining to robot control, achieving strong performa

tutorialsarxiv-cs-cv

VP-EVT: Active Visibility Preservation for Embodied Visual Tracking

arXiv:2610.21999v1 Announce Type: new Abstract: Embodied Visual Tracking (EVT) is an essential capability for intelligent robots in human-robot collaboration, requiring an agent to follow a designated

agentsarxiv-cs-ro

WaveLLM: Wavelet-Domain LLM Entropy Modeling for Lossless Image Compression

model-releasesarxiv-cs-cv

arXiv:2610.22232v1 Announce Type: new Abstract: Lossless image compression fundamentally relies on accurate entropy modeling, driving a recent shift toward large language model (LLM)-based methods. Ho

WEAVE: Weaving Real-World Code Evolution into Dependency-Structured Tasks for Benchmarking and Training Code Agents

arXiv:2610.22039v1 Announce Type: cross Abstract: Real-world software engineering rarely consists of isolated changes. Features, migrations, and systematic fixes often unfold across multiple pull requ

agentsarxiv-cs-cl

When Does 'Post-Call' Begin? An Availability Contract for Earnings-Call NLP Benchmarks

model-releasesarxiv-cs-cl

arXiv:2610.21659v1 Announce Type: cross Abstract: Corporate financial disclosures often unfold over time, with announcements, prepared remarks, and discussion spanning multiple high-frequency return i

When is a better LLM worth paying for? Stochastic Optimization with Switching Mixed-Fidelity Oracles

arXiv:2610.21139v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used upstream of decision-making to clean data, detect label errors, and reconstruct missing values. Yet

Local Ai

When Is Muon Optimal? Radial Fragility and Minimax Geometry

arXiv:2610.21549v1 Announce Type: cross Abstract: Muon replaces a matrix gradient by an approximate polar factor and has shown strong empirical performance in neural-network training. The Isotropic Cu

local-aiarxiv-cs-ai

When Should a Low-Light Pipeline Generate? Auditable Risk Control for Selective Generative Enhancement

arXiv:2610.21335v1 Announce Type: new Abstract: Generative low-light enhancers recover plausible texture but may hallucinate structure; restoration networks preserve structure but can leave regions un

Where, How, and When: Query-Guided Grounding for Video Understanding

arXiv:2610.21422v1 Announce Type: cross Abstract: Understanding video content requires reasoning at multiple levels of granularity, from identifying objects to interpreting their interactions and loca

Where to Steer: Input-Dependent Layer Selection for Steering Improves LLM Alignment

arXiv:2604.03867v2 Announce Type: replace Abstract: Steering vectors have emerged as a lightweight and effective approach for aligning large language models (LLMs) at inference time, enabling modulati

safetyarxiv-cs-lg

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

Whole-Body Dexterity

arXiv:2610.22184v1 Announce Type: cross Abstract: Current humanoid dexterous manipulation remains largely confined to end-effectors and simple grasps, falling short of humans' ability to engage the en

Why Do Agent Teams Fail Across Boundaries? A Failure Taxonomy for Agent-to-Agent Systems with Private States

arXiv:2610.19342v2 Announce Type: replace-cross Abstract: Agents are increasingly interacting with other agents that act for different principals (people or organizations on whose behalf they work), s

agentsarxiv-cs-ai