Search: “inference”

The Deterministic Horizon: Impossibility Results as Design Specifications for Trustworthy AI Systems

arXiv:2605.23024v1 Announce Type: new Abstract: Large language models now write software, draft legal documents, and produce clinical notes, yet fundamental limits, from Turing and Arrow to the No Fre

applicationsarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG

DGX agent

arXiv:2506.04390v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems are vulnerable to attacks that inject poisoned passages into the retrieved context, even at low c

safetyarxiv-cs-ai

25 May 2026

Uncertainty-aware classification and triage of structural heart disease using electrocardiography and echocardiography metrics

arXiv:2605.22968v1 Announce Type: cross Abstract: Machine learning methods provide a methodological innovation that can help screen for cardiovascular disease through noninvasive and readily available

Universal Matrix Multiplication on Quantum Computer

arXiv:2408.03085v3 Announce Type: replace-cross Abstract: As the most central and computationally intensive component of deep neural networks, the execution efficiency of matrix multiplication directl

v0.30.0-rc25

v0.30.0-rc25 is a pre-release version of Ollama that changes the architecture to directly support llama.cpp instead of building on top of GGML, and allows for compatibility with GGUF file format. MLX

local-aiollama-releases

VDE: Training-Free Accelerating Rectified Flow Model via Velocity Decomposition and Estimation

model-releasesarxiv-cs-cv

arXiv:2605.23381v1 Announce Type: new Abstract: Though rectified flow models have achieved remarkable performance in image, video, and 3D generation, their practical deployments are challenged by slow

VGAS: Value-Guided Action-Chunk Selection for Few-Shot Vision-Language-Action Adaptation

arXiv:2602.07399v2 Announce Type: replace Abstract: Vision--Language--Action (VLA) models bridge multimodal reasoning with physical control, but adapting them to new tasks with scarce demonstrations r

researcharxiv-cs-ai

WeCon: An Efficient Weight-Conditioned Neural Solver for Multi-Objective Combinatorial Optimization Problems

arXiv:2605.22876v1 Announce Type: new Abstract: Existing neural solvers for Multi-Objective Combinatorial Optimization Problems (MOCOPs) commonly adopt decomposition-based strategies that scalarize an

LongCat-Video-Avatar 1.5 Release

local-air-stablediffusion

LongCat-Video-Avatar 1.5 is an upgraded open-source framework that prioritizes extreme empirical optimization and production-readiness for audio-driven human video generation. The v1.5 release replace

24 May 2026

v0.30.0-rc24

v0.30.0-rc24 is a pre-release version that changes Ollama's architecture to directly support llama.cpp instead of building on top of GGML, enabling compatibility with the GGUF file format. MLX is used

local-aiollama-releases

24 May 2026

A2QTGN: Adaptive Amplitude Quantum-Integrated Temporal Graph Network for Dynamic Link Prediction

arXiv:2605.21916v1 Announce Type: cross Abstract: Dynamic link prediction is important for modeling evolving interactions in complex systems, including social, communication, financial, and transporta

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations

arXiv:2605.22275v1 Announce Type: new Abstract: Kernel methods are typically formulated under the assumption of exact, noise-free access to the Gram matrix. However, in emerging settings such as quant

b9297

local-aillama-cpp-releases

The search results show information about llama.cpp releases but don't contain specific details about build b9297. Based on the context and numbering (b9297 is a recent build after b9294), b9297 is li

BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series

arXiv:2605.22468v1 Announce Type: new Abstract: Cross-subject generalization in biomedical time-series refers to training on data from some subjects and testing on unseen subjects.The key challenge is

Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes

arXiv:2605.22075v1 Announce Type: new Abstract: Diabetes is a global health burden, and early detection is critical for timely intervention. This study explores a non-invasive, data-driven framework t

Can Transformers Learn to Verify During Backtracking Search?

arXiv:2605.22221v1 Announce Type: new Abstract: Backtracking search underlies classical constraint solvers, planners, and theorem provers. Recent transformer-based reasoning systems explore search tre

local-aiarxiv-cs-lg

ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data

arXiv:2605.21963v1 Announce Type: new Abstract: Long-horizon clinical simulation -- predicting how a patient's physiology evolves over years under specified interventions -- is central to chronic-dise

Correcting Class Imbalance in Prior-Data Fitted Networks for Tabular Classification

arXiv:2605.21742v1 Announce Type: new Abstract: Prior-data fitted networks (PFNs) have achieved exceptional performance on tabular classification tasks. However, like other classifiers, their performa

Dynamic Mixture of Latent Memories for Self-Evolving Agents

arXiv:2605.21951v1 Announce Type: new Abstract: Achieving self-evolution in intelligent agents requires the continual accumulation of new knowledge across changing task sequences without forgetting pr

F-TIS: Harnessing Diverse Models in Collaborative GRPO

arXiv:2605.22537v1 Announce Type: new Abstract: Reinforcement learning methods such as GRPO have seen great popularity in LLM post-training. In GRPO, models produce completions to a set of prompts, wh

local-aiarxiv-cs-lg

Factored Diffusion Policies:Compositionally Generalized Robot Control with a Single Score Network

arXiv:2605.22596v1 Announce Type: new Abstract: Robotic tasks are typically specified by a tuple of factors, such as the object to be grasped, the obstacles to be avoided, the color of the target, and

From Snapshots to Trajectories: Learning Single-Cell Gene Expression Dynamics via Conditional Flow Matching

arXiv:2605.22340v1 Announce Type: new Abstract: Single-cell RNA sequencing (scRNA-seq) provides high-dimensional profiles of cellular states, enabling data-driven modeling of cellular dynamics over ti

Heterogeneous Agent Collaborative Reinforcement Learning

arXiv:2603.02604v2 Announce Type: replace Abstract: We introduce Heterogeneous Agent Collaborative Reinforcement Learning (HACRL), a new Reinforcement Learning from Verifiable Reward (RLVR) problem th

Tutorials

Learning Causal Orderings for In-Context Tabular Prediction

arXiv:2605.22335v1 Announce Type: new Abstract: In-context learning for tabular data sets strong predictive standards in observational settings; it however primarily relies on correlational structure,

tutorialsarxiv-cs-lg

LEMUR: Learned Multi-Vector Retrieval

arXiv:2601.21853v2 Announce Type: replace-cross Abstract: Multi-vector representations generated by late interaction models, such as ColBERT, enable superior retrieval quality compared to single-vecto

Little by Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts

arXiv:2506.21035v5 Announce Type: replace Abstract: Continual learning (CL) with large pre-trained models aims to incrementally acquire knowledge without catastrophic forgetting. Existing LoRA-based M

MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data

arXiv:2605.22775v1 Announce Type: new Abstract: Real-time cognitive load assessment from eye-tracking signals could potentially enable adaptive human-centered-AI such as safety-critical applications s

Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization

arXiv:2605.21751v1 Announce Type: new Abstract: Text-to-optimization requires two separable capabilities: modeling -- choosing the right optimization structure -- and binding -- grounding every coeffi

Physics-Informed Generative Solver: Bridging Data-Driven Priors and Conservation Laws for Stable Spatiotemporal Field Reconstruction

arXiv:2605.22338v1 Announce Type: new Abstract: Reconstructing continuous physical fields from sparse measurements is a central inverse problem, but data-driven generative models can produce states th

Physics Priors Offer Useful Accuracy-Carbon Trade-Offs in Spatio-Temporal Forecasting

arXiv:2509.24517v2 Announce Type: replace Abstract: Development of modern deep learning methods has been driven primarily by the push for improving model efficacy (accuracy metrics). This sole focus o

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices

arXiv:2605.22097v1 Announce Type: cross Abstract: Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challen

Riemannian geometry meets fMRI: the advantages of modeling correlation manifolds and eigenvector subspaces

arXiv:2605.22334v1 Announce Type: new Abstract: Correlation matrices are fundamental summaries of functional brain networks, yet standard analyses often treat entries independently, ignoring the curve

SepsisAI Orchestrator: A Containerized and Scalable Platform for Deploying AI Models and Real-Time Monitoring in Early Sepsis Detection

arXiv:2605.22331v1 Announce Type: new Abstract: Despite strong predictive results in the clinical machine learning literature, the translation of these models into bedside use remains limited by syste

Soft Bayesian Context Tree Models for Real-Valued Time Series

arXiv:2601.11079v2 Announce Type: replace Abstract: This paper proposes the soft Bayesian context tree model (Soft-BCT), which is a novel BCT model for real-valued time series. The Soft-BCT considers

Symbolic Density Estimation for Discrete Distributions

arXiv:2605.21813v1 Announce Type: new Abstract: Discrete probability laws underpin statistical modeling, yet the catalog of interpretable distributions has expanded only gradually through centuries of

Towards Speed-of-Light Text Generation with Nemotron-Labs Diffusion Language Models

model-releaseshugging-face

Nemotron-Labs Diffusion Language Models represent NVIDIA's approach to achieving faster text generation through diffusion-based architectures, potentially offering significant speed improvements over

Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imaging

arXiv:2603.21717v4 Announce Type: replace Abstract: Distribution-to-distribution generative models support scientific imaging tasks ranging from modeling cellular perturbation responses to translating

Uncertainty quantification for Markov chain induced martingales with application to temporal difference learning

arXiv:2502.13822v3 Announce Type: replace-cross Abstract: We establish novel and general high-dimensional concentration inequalities and Berry-Esseen bounds for vector-valued martingales induced by Ma

Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation

arXiv:2605.22765v1 Announce Type: new Abstract: Discrete diffusion models are often trained through clean-data prediction, but the prediction can be used in different ways to define the reverse dynami

Hardware

WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving

arXiv:2512.09472v2 Announce Type: replace-cross Abstract: Deploying multiple models within shared GPU clusters is a key strategy to improve resource efficiency in large language model (LLM) serving. E

hardwarearxiv-cs-lg

What are the Right Symmetries for Formal Theorem Proving?

arXiv:2605.22257v1 Announce Type: new Abstract: Formal theorem provers based on large language models (LLMs) are highly sensitive to superficial variations in problem representation: semantically equi

A Robust Semantic Segmentation Pipeline for the CVPR 2026 8th UG2+ Challenge Track 2

arXiv:2605.22216v1 Announce Type: new Abstract: This report presents our solution for the WeatherProof Dataset Challenge, namely CVPR 2026 8th UG2+ Challenge Track 2: Semantic Segmentation in Adverse

researcharxiv-cs-cv

Action with Visual Primitives

arXiv:2605.22183v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for generalist robotic manipulation. A common design in current architectures m

researcharxiv-cs-ro

BeLink: Biomedical Entity Linking Meets Generative Re-Ranking

arXiv:2605.22501v1 Announce Type: new Abstract: Despite recent progress, Biomedical Entity Linking (BEL) with large language models (LLMs) remains computationally inefficient and challenging to deploy

applicationsarxiv-cs-cl

Comparing LLM and Fine-Tuned Model Performance on NVDRS Circumstance Extraction with Varying Prompt Complexity

model-releasesarxiv-cs-cl

arXiv:2605.21845v1 Announce Type: new Abstract: Suicide is a leading cause of death in the United States, and understanding the circumstances that precede it requires extracting structured information

DeepSeek v4: the most expected open-source model ever released, and the quietest landing

model-releaseslambda-labs

After 15 months of incremental updates, leaks, and rumored leaks, DeepSeek released version 4. It arrived without the fanfare R1 and R1-preview commanded in early 2025. That quiet reception is the mos

Do Vision Models Encode Object-Level Semantic Relatedness? A Cognitive Psychology-Inspired Benchmark

model-releasesarxiv-cs-cv

arXiv:1709.03806v2 Announce Type: replace Abstract: Modern vision models have achieved strong object-recognition performance, yet it remains unclear whether their representations encode object-level s

EntmaxKV: Support-Aware Decoding for Entmax Attention

arXiv:2605.21649v1 Announce Type: cross Abstract: Long-context decoding is increasingly limited by KV-cache memory traffic since each generated token attends over a cache whose size grows linearly wit

researcharxiv-cs-cl