Search: “framework”

arXiv:2609.36929v1 Announce Type: new Abstract: Recent event-based depth estimation methods successfully transfer geometric priors from vision foundation models via cross-modal distillation. However,

applicationsarxiv-cs-cv

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Sharp Convergence and Sampling Trade-offs for Riemannian Diffusion under Nonnegative Ricci Curvature

DGX agent

arXiv:2609.36568v1 Announce Type: new Abstract: Diffusion models have emerged as state-of-the-art generative models, with recent extensions from Euclidean spaces to Riemannian manifolds. However, exis

researcharxiv-cs-lg

30 Sept 2026

Sieve and Sage: Efficient Distraction Filtering for Reliable RALM Abstention

arXiv:2609.35794v1 Announce Type: new Abstract: Just as Socrates recognized the limits of his own knowledge, Retrieval-Augmented Language Models (RALMs) should learn to abstain when the retrieved evid

tutorialsarxiv-cs-cl

SIFARI: Self-Supervised Interferometric Fitting for Astronomical Radio Imaging

arXiv:2609.35966v1 Announce Type: cross Abstract: Radio-interferometric images are reconstructed from sparsely sampled visibilities, and CLEAN-based imaging can struggle with spatial filtering, comple

researcharxiv-cs-lg

Signatures of semantic search in the activations of large language models

arXiv:2609.35599v2 Announce Type: replace Abstract: When recalling lists of concepts (e.g., animals) during the semantic fluency task (SFT), both humans and large language models (LLMs) organise their

safetyarxiv-cs-ai

Skill2Env: Capability-Oriented Environment Synthesis from Skills for General Agents

arXiv:2609.33772v2 Announce Type: replace Abstract: Executable environments are critical for post-training agents on tasks that require tool use and multi-step interaction, but constructing executable

agentsarxiv-cs-ai

SKILLLITE: Evidence-Guided Malicious Skill Auditing with Compact LLMs

arXiv:2609.36879v1 Announce Type: cross Abstract: As LLM-based agents perform increasingly complex tasks, Agent Skills have emerged as a flexible mechanism for extending their capabilities. An Agent S

local-aiarxiv-cs-ai

SkillWeaver: Agentic Exploration over Neural Interaction Skills for Scalable Robot Data Generation

arXiv:2609.36171v1 Announce Type: new Abstract: Large-scale demonstrations have driven unprecedented progress in robot learning, yet collecting robot data through teleoperation is expensive and diffic

agentsarxiv-cs-ro

Socialality Anchors: Towards Group-bounded Trajectory Prediction

arXiv:2609.36852v1 Announce Type: new Abstract: Trajectory prediction is a key component for understanding human behavior patterns in dynamic scenes. Researchers have devoted substantial efforts to mo

agentsarxiv-cs-cv

Soft Curriculum Learning for Optimizing Fresh and Generalized Recommendations

arXiv:2609.35783v1 Announce Type: cross Abstract: Large-scale recommender systems, particularly short-form video platforms, are often bottlenecked by massive popularity feedback loops. In such environ

researcharxiv-cs-lg

Soft yet Effective Robots via Holistic Co-Design

arXiv:2505.03761v2 Announce Type: replace Abstract: Soft robots promise inherent safety via their material compliance for seamless interactions with humans or delicate environments. Despite progress,

safetyarxiv-cs-ro

Industry

Sources: the US FTC is expanding a sweeping probe of Anthropic, OpenAI, and other frontier AI labs, and plans to issue formal demands to turn over information (New York Post)

New York Post: Sources: the US FTC is expanding a sweeping probe of Anthropic, OpenAI, and other frontier AI labs, and plans to issue formal demands to turn over information — WASHINGTON — The Federal

industrytechmeme

Sparse-View Interpretable 3D Animal Behavior Representations for Neural Encoding and Decoding

arXiv:2609.36217v1 Announce Type: new Abstract: A deeper understanding of brain function requires a precise, structured characterization of behavior.Yet, extracting behavioral representations from vid

safetyarxiv-cs-cv

Spatial-OPSD: Self-Improving Spatial Reasoning via Label-Free Self-Distillation

model-releasesarxiv-cs-cv

arXiv:2609.37055v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly operate in embodied and spatially grounded settings, where accurate understanding of depth, viewpoint, and th

SRJudge: Empowering Large Language Models with Selective Reasoning for Fine-Grained Knowledge Concept Tagging

arXiv:2609.36982v1 Announce Type: cross Abstract: Knowledge concept tagging aims to assign specific concept or topic labels to educational content, which is essential for both educators and learners i

Staircase Policy: Streaming Inference for World-Action Models with Large Action Chunks

arXiv:2609.36471v1 Announce Type: cross Abstract: World-Action Models (WAMs) improve robotic manipulation by conditioning action generation on predicted future observations, but future prediction adds

safetyarxiv-cs-ai

StateTape: Action-Conditioned Evidence Lifecycle Modeling for Long-Horizon Coding Agents

arXiv:2609.36319v1 Announce Type: new Abstract: Despite the recent success of coding agents built on large language models, it remains challenging to run them over long horizons, since every observati

Hardware

STEPQuant: When and Where Errors Matter in Delta-Rule Recurrent State Quantization

arXiv:2609.38169v1 Announce Type: cross Abstract: Linear attention replaces growing KV caches with fixed-size recurrent states, yet these persistent states can become a substantial memory bottleneck u

hardwarearxiv-cs-ai

StructRL: Online Structured Reinforcement Learning for Long-Horizon Vision-Language-Action Tasks

arXiv:2609.36352v1 Announce Type: new Abstract: Vision-language-action (VLA) models perform well on shorter-horizon manipulation tasks but still struggle with long-horizon tasks that require multiple

SYNCR: Diagnosing and Learning Cross-Video Reasoning from Simulation

arXiv:2609.37918v1 Announce Type: new Abstract: Reasoning across videos requires aligning events, matching identities, comparing motion, and integrating partial observations. Evaluating these capabili

tutorialsarxiv-cs-cv

T^2Mem: Learning Test-Time Memory for Robotics

model-releasesarxiv-cs-ro

arXiv:2609.36720v1 Announce Type: new Abstract: Memory-dependent robotic manipulation requires policies to use information that is no longer available in the current observation. Retaining history alo

TabKD: Tabular Knowledge Distillation through Interaction Diversity of Learned Feature Bins

arXiv:2603.15481v3 Announce Type: replace-cross Abstract: Data-free knowledge distillation enables model compression without original training data, critical for privacy-sensitive tabular domains. How

TAEC: Trajectory-Aware Evidence Coordination for Multi-Step Visual RAG

arXiv:2609.37349v1 Announce Type: cross Abstract: Multi-step visual retrieval-augmented generation (RAG) answers complex questions by repeatedly retrieving visual evidence, updating an intermediate st

TagPR: Tag-Guided Process Supervision for Personalization Reasoning in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2509.23140v2 Announce Type: replace Abstract: Recent advancements have endowed Large Language Models with impressive general reasoning capabilities. However, these reasoning models often perform

Targeting Pivotal Decisions for Credit Assignment in Agentic Reinforcement Learning

arXiv:2609.36178v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has become a promising approach for training large language model agents. However, its uniform assignment of

local-aiarxiv-cs-ai

TaRL: Learning General and Physical Rewards from Tactile Demonstrations

arXiv:2609.36785v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to sequence precise contacts, maintain stable grasps, and apply directed forces. Reinforcement learning (RL) c

local-aiarxiv-cs-ro

Task-Relevant Null-Space Residuals for Non-Injective Neural Mappings

arXiv:2609.37272v1 Announce Type: new Abstract: Non-injective mappings in neural networks map distinct inputs to the same representation, thereby implicitly inducing equivalence relations in the input

Applications

TaskBridge: Bridging Unsupervised Tabular Anomaly Detection and In-Context Learning via Virtual Tasks

arXiv:2609.36968v1 Announce Type: new Abstract: Unsupervised tabular anomaly detection (TAD) aims to identify anomalous rows in tabular data using normal training samples. While conventional methods r

applicationsarxiv-cs-lg

Temporal-Aware Fusion for Robust Outdoor LiDAR Localization

arXiv:2609.36432v1 Announce Type: new Abstract: LiDAR relocalization aims to estimate the global 6-DoF pose of a sensor in the environment. However, existing regression-based approaches often encounte

Think Before You Restore: Risk-Aware Manchu Manuscript Restoration with Stroke-Guided Attention

arXiv:2609.36243v1 Announce Type: cross Abstract: Full-page blind restoration of historical Manchu manuscripts is challenging due to scarce annotations, unknown degradation regions, and fragile connec

Think, Then Look: Active Spatial Reasoning for House-Scale 3D Scene Understanding

model-releasesarxiv-cs-cv

arXiv:2512.03284v2 Announce Type: replace Abstract: Spatial reasoning in large-scale 3D environments remains challenging for current vision--language models, which are typically constrained to room-sc

ThinkingGuard: Decoding Implicit Hazards via Step-by-Step Risk Attribution in Multimodal Large Language Models

arXiv:2609.36562v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, their reliability is threatened by multimodal imp

safetyarxiv-cs-ai

ThuRunel: Dynamic Decoupling for Structured Advisory Dialogue

arXiv:2609.36340v1 Announce Type: new Abstract: High-stakes advisory domains such as medical aesthetics, legal consultation, and educational planning exhibit a two-phase structure. The early phase req

agentsarxiv-cs-ai

Time-Anchored Diffusion Language Models: Latent-Space Caching for Fast Generation

arXiv:2609.37924v1 Announce Type: cross Abstract: Recent work on anchored diffusion language models improves denoising by shaping an intermediate latent space with supervised important-token targets.

researcharxiv-cs-cl

TORQUE: Optimizing What (not) to Quantize Before and After Rotation

arXiv:2609.36032v1 Announce Type: cross Abstract: Uniform random rotations are an effective preprocessing step for quantization: they make normalized coordinate distributions approximately Gaussian, e

Toward a Culturally Adapted Chinese Language Agent: A Wizard-of-Oz Study of Nonverbal Behavior in Chinese-German Intercultural Interaction

arXiv:2609.35150v1 Announce Type: cross Abstract: Successful intercultural communication requires more than grammatical competence. It demands sensitivity to culturally embedded social norms whose vio

agentsarxiv-cs-cl

Towards Scalable Context-Aware Single-Cell Spatial Transcriptomics Prediction from Histology Images

arXiv:2609.36429v1 Announce Type: new Abstract: Predicting gene expression from H&E-stained histology images offers a scalable alternative to costly spatial transcriptomics, yet most existing methods

local-aiarxiv-cs-cv

TRACE: Deployable Tree-Relational Structure Enhancement for Oncology LLMs

arXiv:2609.35810v1 Announce Type: cross Abstract: Large language models are increasingly used in oncology applications, but their predictions are often weakly grounded in explicit medical structure. W

Tracing the Evidence: Faithful Token Attribution Through Vision-Language Reasoning

arXiv:2609.37656v1 Announce Type: new Abstract: Large vision-language models (LVLMs) exhibit strong reasoning capabilities, yet the visual and textual evidence supporting the generated responses remai

Training-Free Global Geometric Association for 4D LiDAR Panoptic Segmentation

arXiv:2512.18991v3 Announce Type: replace-cross Abstract: Dominant paradigms for 4D LiDAR panoptic segmentation are usually required to train deep neural networks with large superimposed point clouds

researcharxiv-cs-ai

Trajectory-Level Mode Guidance for Controllable Diffusion-Based Multi-Robot Motion Planning

arXiv:2609.36530v1 Announce Type: new Abstract: Motion planning often admits multiple feasible solutions, making multimodal generation valuable, particularly for flexible multi-robot coordination. Dif

agentsarxiv-cs-ro

Traversing the solution space of neural networks with Hessian Null Space Continuation

arXiv:2609.38081v1 Announce Type: new Abstract: On a single task, deep networks can learn many solutions, depending on their optimizer, training data, architecture, and hyperparameters. Many of these

local-aiarxiv-cs-lg

TReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning

arXiv:2609.37581v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visua

researcharxiv-cs-ai

TTMark: Pairwise Distortion-Free Watermarking Beyond Single-Token Entropy

arXiv:2609.36372v1 Announce Type: cross Abstract: Distortion-free watermarking enables reliable attribution of machine-generated text while preserving output distribution. However, existing methods op

researcharxiv-cs-cl

UltraMatch: Transport Path Routing for Ultra-Fast and Memory-Efficient Image Matching

arXiv:2609.36980v1 Announce Type: new Abstract: Despite recent advances in accuracy and efficiency, coarse matching remains an indispensable yet costly stage in existing semi-dense matchers due to den

UNBIND: UNlearning By INference-time Directional Steering for Code LLMs

arXiv:2609.35913v1 Announce Type: cross Abstract: Code large language models acquire programming capabilities from large code corpora, but can also memorize implementations that later require removal.

UniAfford: Token-Routed Multitask Learning for Generalizable 2D-3D Affordance Perception

arXiv:2609.37264v1 Announce Type: cross Abstract: Affordance perception aims to localize actionable regions supporting embodied interaction, yet 2D and 3D affordance grounding have evolved as separate

local-aiarxiv-cs-ai

UniBuild: Unified Building Mapping From Multi-Source Optical Remote Sensing Imagery With Detail Decoding and Geometry Regularization

model-releasesarxiv-cs-cv

arXiv:2609.37031v1 Announce Type: new Abstract: Building extraction from optical remote sensing (RS) imagery is fundamental to urban mapping, yet existing methods are often dataset-specific and genera