Search: “inference”

LLM Agents Factory: Retrieval of Domain-Specific LLM Agents

arXiv:2608.09934v1 Announce Type: cross Abstract: Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors. However, their practical deploymen

agentsarxiv-cs-ai

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Lost in Reconstruction: Aligning Action Representations with Language in Vision-Language-Action Models

DGX agent

arXiv:2608.10484v1 Announce Type: cross Abstract: Action verbs describe not only the physical outcomes of actions, but also how those actions are performed. Yet action representations in vision-langua

researcharxiv-cs-ai

12 Aug 2026

Applications

MammoMix: Leveraging Mixture of Experts for Robust Mammogram Breast Detection

arXiv:2608.10437v1 Announce Type: new Abstract: Breast lesion detection in mammography remains a challenging task due to variations in image quality, lesion appearance, and population demographics acr

applicationsarxiv-cs-cv

Mapping and Measuring the Behavioral Evolution of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.11027v1 Announce Type: cross Abstract: Benchmark leaderboards summarize how well a language model performs, but not how its behavior relates to that of other models or changes across genera

Applications

MazzikaAI: A knowledge-based performance-to-prompt compiler for real-time Arabic maqam accompaniment with a streaming text-to-music model

arXiv:2608.10360v1 Announce Type: cross Abstract: Arabic maqam music microtonal, modal, and built on ornamented call and response is among the traditions most underserved by generative music models, w

applicationsarxiv-cs-ai

Mitigating Bus Bunching with Reinforcement Learning Enhanced by Semantic Stop Embedding

arXiv:2608.10207v1 Announce Type: new Abstract: Bus bunching degrades service regularity and increases passenger waiting in high-frequency transit. Existing reinforcement-learning-based holding contro

Multi-View Relational Distillation for Spatial Reasoning with Vision-Language Models

arXiv:2608.10864v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong image and video understanding, yet their visual-spatial representations remain geometrically fragile,

safetyarxiv-cs-cv

MultiModal Code-Switching: Interleaving Visual Objects into Language for Explicit Object-Level Alignment

arXiv:2608.11167v1 Announce Type: cross Abstract: Existing Multimodal Large Language Models (MLLMs) predominantly rely on image-text pairs for modality alignment pretraining, mapping global image repr

local-aiarxiv-cs-cl

NullEdit: Stealthy Image Protection via VLM Condition Redirection

arXiv:2608.10870v1 Announce Type: new Abstract: Modern image editors combine vision-language models (VLMs) with diffusion transformer backbones to modify a single reference image according to instruct

OmniVTA: Visuo-Tactile World Modeling for Contact-Rich Robotic Manipulation

arXiv:2603.19201v3 Announce Type: replace Abstract: Contact-rich manipulation tasks, such as wiping and assembly, require accurate perception of contact forces, friction changes, and state transitions

safetyarxiv-cs-ro

Tutorials

Once Poisoned, Arbitrarily Controlled: A Programmable Backdoor in VLMs

arXiv:2608.10959v1 Announce Type: new Abstract: Existing vision-language model (VLM) backdoors are usually treated as static vulnerabilities: one-to-one and N-to-N attacks bind one or more triggers to

tutorialsarxiv-cs-cv

PEAK: Precise and Persistent Concept Erasure via k-Sparse Autoencoders

arXiv:2608.10985v1 Announce Type: new Abstract: Erasing concepts from large-scale text-to-image (T2I) diffusion models has become increasingly crucial due to the growing concerns over copyright infrin

Physics-Informed Machine Learning in Prognostics and Health Management: A Systematic Literature Review

arXiv:2608.10047v1 Announce Type: cross Abstract: In modern industry, keeping complex systems reliable, safe, and efficient hinges on Prognostics and Health Management (PHM). Machine Learning (ML) has

Pre- to Post-Contrast Synthesis of Breast DCE-MRI using Latent Bridge Matching

arXiv:2608.10000v1 Announce Type: cross Abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is central to breast cancer imaging, but gadolinium administration increases scan burde

researcharxiv-cs-cv

Qwen3.8-Max is live on Together AI on day zero. Proud to have supported early testing alongside @Alibaba_Qwen, @vllm_project, and Inferact t…

model-releasestogether-ai--x

Qwen3.8-Max is live on Together AI on day zero. Proud to have supported early testing alongside @Alibaba_Qwen, @vllm_project, and Inferact to get day-zero support live. We’re continuing to optimize pe

Tutorials

Rationale-Guided Learning for Multimodal Emotion Recognition

arXiv:2608.10448v1 Announce Type: new Abstract: Multimodal emotion recognition in conversation (MERC) requires understanding complex interactions between verbal and non-verbal cues. However, most exis

tutorialsarxiv-cs-ai

ReRound: Reconstructive Rounding to Resolve Midpoint Ambiguity in Calibration-Free LLM Quantization

model-releasesarxiv-cs-cl

arXiv:2608.11045v1 Announce Type: cross Abstract: ReRound (Reconstructive Rounding) is a post-training quantization method that addresses the midpoint ambiguity inherent in standard round-to-nearest (

Rescene: band-limited stochastic forcing turns a frozen neural weather operator into a climate emulator

arXiv:2608.09971v1 Announce Type: cross Abstract: Over the past few years, the rapid development of machine learning (ML) models for weather forecasting has produced deterministic models whose medium-

Retrieval-Corrected Conformal Prediction for Time Series

arXiv:2608.10553v1 Announce Type: cross Abstract: Conformal prediction (CP) provides distribution-free prediction intervals for fixed forecasters, but its standard calibration procedure is often ineff

local-aiarxiv-cs-ai

Sensor-Informed Per-Point Covariance for Structured-Light 3D Imaging

arXiv:2608.10888v1 Announce Type: new Abstract: Per-point uncertainty models are important in structured-light 3D reconstruction for probabilistic registration, fusion, and quality assessment. In prac

local-aiarxiv-cs-cv

Seq2Synth: Benchmarking Temporal Fidelity in Synthetic Sequential Tabular Data

model-releasesarxiv-cs-lg

arXiv:2607.15606v2 Announce Type: replace Abstract: Synthetic sequential tabular data are increasingly used for privacy-preserving data sharing and data-driven research, but evaluating their fidelity

Serve Qwen3.8-2.4T-A95B, a 2.4T-Parameter Model, with Configurable Reasoning on NVIDIA GB300 NVL72

model-releasesnvidia-developer

Alibaba released the open‑weights Qwen3.8‑2.4T‑A95B (Qwen3.8‑Max), a fine‑grained mixture‑of‑experts model with 2.4 trillion parameters, hybrid full‑ and linear‑attention, a one‑million‑token context

Share First, Route What Remains: A Unified Framework for Token-Adaptive MoE Computation

arXiv:2608.10392v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models have recently moved beyond routing a fixed number of complete experts. Shared-expert designs preserve reusable knowled

researcharxiv-cs-cl

Significance and Stability Analysis of Gene-Environment Interaction using GxEStat

arXiv:2604.03337v2 Announce Type: replace Abstract: Genotype-environment (GxE) interactions can influence the performance of genotypes across diverse environments, limiting the reliability of genotype

SKILLER: Language-Level Reinforcement Learning for Reusable Skill Extraction in Small Language Models

arXiv:2608.10538v1 Announce Type: new Abstract: Agent skills represent a standardized format for packaging procedural knowledge and domain expertise, serving within agent harness systems as an essenti

agentsarxiv-cs-ai

SkillLens: Visual Skill Cards for Retrieval-Augmented GUI Action Prediction and On-Policy Distillation

arXiv:2608.10775v1 Announce Type: new Abstract: Computer-using agents can perceive rich software interfaces, yet their decisions often lack visual procedural memory: they may recognize individual cont

SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information

arXiv:2608.10692v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across

Status Association Does Not Reliably Predict Decision Leakage

arXiv:2608.10089v1 Announce Type: cross Abstract: Bias evaluations often move too quickly from evidence that a model encodes a social association to claims that the same association will alter consequ

STCAD: Scalable Trajectory Clustering and Anomaly Detection on Terabyte-Scale AIS Data

arXiv:2608.10249v1 Announce Type: new Abstract: We present a scalable framework for unsupervised clustering of maritime trajectories derived from terabyte-scale Automatic Identification System (AIS) a

researcharxiv-cs-lg

SuperQuadricOcc: Real-Time Self-Supervised Semantic Occupancy Estimation with Superquadric Volume Rendering

arXiv:2511.17361v5 Announce Type: replace Abstract: Self-supervision for semantic occupancy estimation is appealing as it removes the labour-intensive manual annotation, thus allowing one to scale to

agentsarxiv-cs-cv

SynBoost: A Synergistic Framework for Fast Sampling of Diffusion Models

arXiv:2506.13058v2 Announce Type: replace-cross Abstract: Diffusion probabilistic models (DPMs) have demonstrated remarkable success in visual generation. However, their iterative sampling mechanism r

TEASR: Training-Efficient Any-Step Diffusion Transformer for Real-World Image Super-Resolution

arXiv:2606.16188v2 Announce Type: replace Abstract: Diffusion models excel in Real-World Image Super-Resolution (Real-ISR) due to their powerful generative priors but suffer from slow iterative sampli

The Deliberative Deficit: An Empirical Critique of LLMs in Democratic Discourse

arXiv:2608.10186v1 Announce Type: cross Abstract: LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems. Confidence in these deployments rests l

agentsarxiv-cs-ai

The Epistemic Politics of AI Anthropomorphism

arXiv:2608.00961v2 Announce Type: replace-cross Abstract: AI anthropomorphism is typically treated as a problem of user misperception requiring institutional correction. Users who engage in sustained

The Gaussian-Multinoulli Restricted Boltzmann Machine: A Potts Model Extension of the GRBM

arXiv:2505.11635v2 Announce Type: cross Abstract: Many real-world tasks, from associative memory to symbolic reasoning, benefit from discrete, structured representations that standard continuous laten

The Impact of Operational-Data Fidelity when Assessing Safety-Critical Autonomous-Vehicle Software

arXiv:2608.10025v1 Announce Type: new Abstract: For safety-critical software, data from the software's operational past (e.g. a sequence of success and failure events experienced by the software) can

safetyarxiv-cs-ro

The Multilingual Quantization Tax: Structural Collapse and Typological Fragility in Edge SLMs

model-releasesarxiv-cs-cl

arXiv:2608.09941v1 Announce Type: new Abstract: While 4-bit weight quantization is critical for deploying Small Language Models (SLMs) on edge devices, evaluations of the resulting performance degrada

The Parser Already Knows: Lightweight Bias Correction in Constrained Decoding

arXiv:2608.10137v1 Announce Type: new Abstract: Grammar Constrained Decoding (GCD) forces Language Models (LMs) to produce syntactically valid outputs by masking out non-conforming tokens at each step

safetyarxiv-cs-cl

Token-Based Detection of Spurious Correlations in Vision Transformers

arXiv:2509.04009v2 Announce Type: replace-cross Abstract: Due to their powerful feature association capabilities, neural network-based computer vision models have the ability to detect and exploit uni

local-aiarxiv-cs-ai

TRACE-GS: On-Policy Trajectory Distillation with Privileged Geometric Conditioning for Sparse-View 3DGS Restoration

arXiv:2608.10286v1 Announce Type: new Abstract: We present TRACE-GS, an on-policy trajectory distillation framework that leverages privileged geometric conditioning at training time, thereby adapting

safetyarxiv-cs-cv

v0.32.10

model-releasesollama-releases

What's Changed Models that don't set a repeat_penalty now default to 1.0 (off) instead of 1.1, matching other engines and speeding up speculative decoding; set a per-model parameter if an older model

With the smartest person I know, @HarshSensei, we're building evsys-sdk for the community, this open-source repository allows anyone to buil…

model-releasesfireworks-ai--x

With the smartest person I know, @HarshSensei, we're building evsys-sdk for the community, this open-source repository allows anyone to build their own continual learning system with first-class suppo

4D-WAM: Infusing Spatiotemporal Awareness into World Action Models through Trajectory Fields

arXiv:2608.08023v1 Announce Type: new Abstract: Building on recent advances in world models, World Action Models (WAMs) jointly model video prediction and action generation. However, they typically re

local-aiarxiv-cs-ro

A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization

arXiv:2608.08156v1 Announce Type: new Abstract: In evolutionary algorithms powered by language models, the LLM acts as a single operator that simultaneously updates structural components (like control

researcharxiv-cs-lg

A Minimal kappa--au Logic for Risk-Sensitive Abduction

arXiv:2608.08192v1 Announce Type: new Abstract: Standard approaches to abductive reasoning can retain multiple candidate explanations, but they do not generally combine explicit compositional cross-hy

A Semantic Communication Approach to Fiducial Marker Processing in 5G-Enabled Edge SLAM

arXiv:2608.09620v1 Announce Type: cross Abstract: Autonomous robots increasingly rely on edge computing to offload computationally intensive perception tasks while maintaining real-time operation over

agentsarxiv-cs-ro

A Sobering Look at Tabular Data Generation via Probabilistic Circuits

arXiv:2603.23016v2 Announce Type: replace-cross Abstract: Tabular data is more challenging to generate than text and images, due to its heterogeneous features and much lower sample sizes. On this task

A Unified Framework for Dynamic Reward Shaping in Reinforcement Learning

arXiv:2608.08158v1 Announce Type: new Abstract: Sparse, delayed, and weakly informative rewards remain central obstacles to efficient reinforcement learning. Reward shaping addresses these limitations