Search: “framework”

Rethinking Correctness for Uncertainty Estimation in Clinical Prediction with Vision-Language Models

arXiv:2609.15180v1 Announce Type: new Abstract: Vision-language models are increasingly explored for clinical prediction from electronic health records and medical images, where identifying unreliable

researcharxiv-cs-lg

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Retrieval-Guided Fine-Tuning as Noisy Estimation: Risk bounds and Architectural Analysis

DGX agent

arXiv:2609.14485v1 Announce Type: new Abstract: Retrieval-Guided Fine-Tuning (RAG-FT) incorporates retrieved data directly into the training objective, but the statistical consequences of noisy retrie

safetyarxiv-cs-lg

15 Sept 2026

Robust and Efficient Communication for Multi-Agent Learning

arXiv:2609.15361v1 Announce Type: cross Abstract: Effective communication is a cornerstone of distributed intelligence in Multi-Agent Reinforcement Learning (MARL), yet ensuring that generated message

agentsarxiv-cs-ai

Robust Multi-Model Fitting through Learning Neighbor Regions

arXiv:2609.15348v1 Announce Type: new Abstract: Multi-model fitting involves fitting multiple models accurately in a noisy environment. It is the basis for computer vision tasks such as scene reconstr

RSIAgent: Autonomous Exploration for Recursive Self-improvement in New Environments

arXiv:2609.15364v1 Announce Type: new Abstract: Digital agents must often adapt to new environments whose interfaces, tools, and failure modes are not fully captured by pretrained models. We introduce

agentsarxiv-cs-ai

Safe Meta-Reinforcement Learning via Information Space Reachability

arXiv:2609.15915v1 Announce Type: new Abstract: Meta-reinforcement learning (meta-RL) enables agents to adapt to unseen tasks with limited experience. Despite its promise, the application of meta-RL i

safetyarxiv-cs-lg

SAM3D-Part: Interactive Part Selection and Generation from 3D Objects

arXiv:2609.15639v1 Announce Type: new Abstract: Part-level control is essential for modern 3D asset creation, where objects are frequently edited, reused, animated, or fabricated through their individ

safetyarxiv-cs-cv

Sampling headroom is not selection gain: a compute-value audit of test-time scaling for video world models

arXiv:2609.13257v1 Announce Type: cross Abstract: Test-time scaling (TTS) can improve generation only when additional compute produces better candidates and the system can reliably identify them. This

SCOUT-SLAM: Structurally-Coupled Dual Uncertainty-Aware 3DGS SLAM in the Wild

arXiv:2609.14634v1 Announce Type: new Abstract: Recently, 3D Gaussian Splatting SLAM (3DGS-SLAM) has gained significant momentum in simultaneous localization and 3DGS scene reconstruction. In real-wor

SEA-Nav: Efficient Policy Learning for Safe and Agile Quadruped Navigation in Cluttered Environments

arXiv:2603.09460v2 Announce Type: replace Abstract: Efficiently learning safe and agile quadruped navigation in densely cluttered environments remains difficult: existing methods often lack safety and

safetyarxiv-cs-ro

Self-Evolving Memory for Generative Recommendation

arXiv:2609.15598v1 Announce Type: cross Abstract: Generative recommendation has emerged as a promising end-to-end paradigm for personalized recommendation. However, user preferences continuously evolv

Self-Indexing Attention for Compression-Compatible Sparse Long-Context LLM Inference

arXiv:2609.13205v1 Announce Type: cross Abstract: Sparse long-context inference requires efficient token retrieval in both prefill and decode. Existing methods often use different retrieval strategies

researcharxiv-cs-cl

Semantic Fibers and Cross-Gram Interference: A Calculus of Safety Drift in Overcomplete Representations

arXiv:2609.14861v1 Announce Type: cross Abstract: A deployed language model may refuse a harmful request in English yet comply with its faithful translation, revealing a cross-lingual safety failure t

safetyarxiv-cs-ai

Semantic Privacy Protection with Utility Preservation for 3D Point Clouds

model-releasesarxiv-cs-cv

arXiv:2609.13823v1 Announce Type: new Abstract: Point cloud data face serious semantic privacy risks during acquisition, transmission, and cross-institutional sharing. Existing methods mostly rely on

Semiotic Relations and Proof Methods: A Cross-Genre Study of Argument Structure with Large Language Models

arXiv:2609.15194v1 Announce Type: new Abstract: When a direct proof of a statement S seems hard or even impossible to obtain, there may exist another statement (or set of statements) S^{*}, somehow re

applicationsarxiv-cs-cl

Sensory Precision Inference for Multimodal Arbitration under Uncertainty

arXiv:2609.15065v1 Announce Type: new Abstract: Autonomous agents operating on multisensory data cannot assume that all sensory modalities remain consistently informative. In real environments, sensor

agentsarxiv-cs-lg

Tutorials

SeqMaestro: From nucleotide sequences to biological hypotheses through interpretable machine learning

arXiv:2609.14882v1 Announce Type: cross Abstract: Nucleotide sequence analysis is central to problems spanning regulatory genomics, evolutionary biology, and phenotype prediction. Classical bioinforma

tutorialsarxiv-cs-ai

SGWIB:Sliced Gromov-Wasserstein Information Bottleneck for Video Highlight Detection

arXiv:2609.13966v1 Announce Type: cross Abstract: Video highlight detection aims to identify temporally important segments that capture the most informative or engaging events in a video. Reliable pre

safetyarxiv-cs-ai

Single-step Diffusion-based Video Coding with Semantic-Temporal Guidance

arXiv:2512.07480v2 Announce Type: replace Abstract: While traditional and neural video codecs (NVCs) have achieved remarkable rate-distortion performance, improving perceptual quality at low bitrates

researcharxiv-cs-cv

SlopShape: Identifying AI-Generated Commercial Web Content

arXiv:2609.15369v1 Announce Type: new Abstract: Word-level detectors identify unedited AI-generated text almost perfectly, but the literature documents their brittleness under rewording, and a word-le

researcharxiv-cs-cl

Solar Intelligence

arXiv:2609.13648v1 Announce Type: new Abstract: Solar energy decision support is fragmented across dashboards that provide data without explanation, research papers are slow to parse, and general-purp

agentsarxiv-cs-ai

SPARK: Representation-Level KV Memory Alignment for Safer Vision-Language Models

arXiv:2609.14258v1 Announce Type: new Abstract: Vision-language models (VLMs) remain vulnerable to jailbreaks that distribute harmful intent across text and images, making unimodal safety mechanisms i

safetyarxiv-cs-cv

Speak to the City: Multimodal Resolution for Outside-the-Vehicle References

arXiv:2609.14691v1 Announce Type: cross Abstract: As autonomous vehicles and Extended Reality (XR) headsets enable novel in-car interactions, seamlessly querying physical landmarks, known as Outside-t

agentsarxiv-cs-cl

SpermYOLO: A Coordinated YOLO-Based Detector for Accurate and Efficient Sperm and Impurity Detection in Microscopic Images

arXiv:2609.14278v1 Announce Type: cross Abstract: Accurate sperm detection is essential for computer-assisted semen analysis, yet it remains challenging in microscopic images due to dense distribution

SPICE: Simple Polysemantic Feature Interpretation via Clustering-based Explanation

arXiv:2609.13198v1 Announce Type: cross Abstract: One of the pivotal recent challenges in neural network interpretability is polysemanticity, where a single neuron is activated by multiple, often unre

researcharxiv-cs-cv

Stable Walking for Bipedal Locomotion under Foot-Slip via Virtual Nonholonomic Constraints

arXiv:2603.29050v2 Announce Type: replace-cross Abstract: Foot slip is a major source of instability in bipedal locomotion on low-friction or uncertain terrain. Standard control approaches typically a

researcharxiv-cs-ro

Steady-State Convergence of Stochastic Approximation

arXiv:2609.14922v1 Announce Type: cross Abstract: For constant-stepsize stochastic approximation (SA), the iterates converge in distribution to a stationary law that depends on the stepsize alpha. Ste

safetyarxiv-cs-lg

Stellar Colosseum: A Many-Agent Harness for Long-Horizon Research in Mathematics and Theoretical Computer Science

arXiv:2609.15983v1 Announce Type: new Abstract: Language models can produce plausible short proofs, but may still be unreliable on long-horizon research problems, where progress depends on a sequence

STHMoE: Hypergraph-Enhanced Heterogeneous Dependency Coordination for LLM-Based Urban Traffic Data Forecasting

arXiv:2609.15172v1 Announce Type: new Abstract: Spatio-temporal traffic forecasting is a fundamental big data analytics task for intelligent transportation systems, where massive urban sensor streams

applicationsarxiv-cs-ai

Structure-Token Evidence-Anchored Reasoning for Scientific Chart Understanding

model-releasesarxiv-cs-cv

arXiv:2609.13267v1 Announce Type: new Abstract: Scientific charts encode quantities in axes, legends, and geometric marks, yet large vision-language models still treat them as natural photographs. Vis

SURE-Map: Self-Correcting Streaming Geometric Foundation Model

arXiv:2609.15795v1 Announce Type: new Abstract: Streaming geometric foundation models are emerging as a compelling alternative to SLAM systems. Yet this streaming nature introduces a fundamental issue

Survey of Novel Deep Learning Architectures for Denoising Gravitational-wave Signals

model-releasesarxiv-cs-lg

arXiv:2609.13272v1 Announce Type: cross Abstract: Gravitational-wave denoising must handle the full diversity of spinning, precessing binaries, since the recovered waveform underpins parameter estimat

Symmetries and Singularities

model-releasesarxiv-cs-lg

arXiv:2609.14663v1 Announce Type: new Abstract: Deep neural networks are highly over-parameterized, and different parameter values represent the same predictive function. This makes their effective co

SyRHM: Symbolic-Language-Enhanced Reasoning with Associative Retrieval for Zero-shot Harmful Meme Detection

arXiv:2609.13794v1 Announce Type: new Abstract: Detecting harmful memes is critical for maintaining safe online communities. However, harmful intent is often implicit, arising from visual-textual inco

researcharxiv-cs-cl

Tackling Failure Modes of PINNs and PIKANs Using Conflict-Free Gradients

arXiv:2609.14841v1 Announce Type: new Abstract: Scientific machine learning methods such as physics-informed neural networks (PINNs) increasingly rely on domain decomposition for better scalability wh

researcharxiv-cs-lg

Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning

arXiv:2509.18930v4 Announce Type: replace-cross Abstract: Neural algorithmic reasoning (NAR) is a paradigm that trains neural networks to execute classic algorithms by supervised learning. Despite its

Task-Distribution-Aware Counterweight Synthesis and Constrained Co-Design for Serial Manipulators

arXiv:2609.15082v1 Announce Type: cross Abstract: Passive counterweights are simple gravity compensators, but a counterweight selected from a single pose is not generally optimal for the configuration

applicationsarxiv-cs-lg

Task-Specified Active Metrological Inspection with Measurement-Steered VLA Manipulation and Deterministic Evidence Gating

arXiv:2609.14219v1 Announce Type: cross Abstract: High-mix low-volume (HMLV) manufacturing requires inspection systems to adapt to changing parts, specifications, and work orders without repeated task

applicationsarxiv-cs-ai

TATK: Triple-Aware Top-K Learning with Knowledge-Grounded Verification for LLM-based Sequential Recommendation

model-releasesarxiv-cs-cl

arXiv:2609.14565v1 Announce Type: new Abstract: LLM-based sequential recommenders usually cast next-item prediction as text generation, but this interface is poorly matched to full-catalog top-K ranki

Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks

arXiv:2505.20132v2 Announce Type: replace-cross Abstract: Tensorizing a neural network involves reshaping some or all of its dense weight matrices into higher-order tensors and approximating them usin

The average-farmer illusion in language-model simulations of agricultural decisions

arXiv:2609.15038v1 Announce Type: new Abstract: Language-model agents are increasingly used as synthetic people in surveys and social simulations, yet their apparent realism is often judged from popul

The Language-Energy Divide: Measuring Energy Costs of Multilingual LLM Inference

arXiv:2606.21869v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed in multilingual settings, yet the energy costs of serving these models across different

The Misery of Mechanistic Interpretability: A Formal Perspective

arXiv:2609.15533v1 Announce Type: cross Abstract: Mechanistic interpretability has become the dominant lens for understanding frontier language models, as their inner workings are complex and inherent

Through the Eyes of the Beholder: Biometric and Demographic Conditioning for Multimodal Sexism Detection

arXiv:2609.15608v1 Announce Type: cross Abstract: Detecting sexism on the internet is a fundamentally subjective task; our team, VANGUARD, addresses this challenge in the EXIST 2026 Task 2 by proposin

Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarks

arXiv:2504.07099v5 Announce Type: replace-cross Abstract: Frequency-domain analysis has emerged as a powerful paradigm for time series analysis, offering unique advantages over traditional time-domain

researcharxiv-cs-lg

To Each Language Its Tokenizer: Modular Tokenizers for Efficient Multilingual LLMs

arXiv:2609.15528v1 Announce Type: new Abstract: Multilingual Large Language Models (LLMs) traditionally rely on a single vocabulary shared by all supported languages, which can lead to uneven compress

safetyarxiv-cs-cl

TopoRig: Topology-Agnostic Facial Rigging via Multi-Source Supervision

arXiv:2609.15746v1 Announce Type: cross Abstract: Automatic facial rigging across heterogeneous mesh topologies remains challenging because high-quality expression supervision is often tied to canonic

Toward Secure Code Generation: Bridging Correctness and Security via Task-Adaptive Vulnerability Modeling and Execution-Based Benchmarking

model-releasesarxiv-cs-cl

arXiv:2407.02395v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for program synthesis, yet they often generate code that is functionally plausible but inse