Search: “inference”

LexKairos: Benchmarking Legal Temporal Capabilities in LLMs

model-releasesarxiv-cs-cl

arXiv:2608.09106v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong performance across a wide range of legal tasks. In legal practice, time is a critical concept that

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LIBAD: A Multimodal Anomaly Detection Benchmark for Li-Ion Battery Electrode Manufacturing

DGX agent

arXiv:2608.07958v1 Announce Type: new Abstract: Multimodal industrial anomaly detection has largely focused on discrete products using strongly correlated RGB and 3D observations, leaving continuous p

model-releasesarxiv-cs-cv

11 Aug 2026

LITEWAY: LIghtweight HAR via Temporal Efficient highWAY

arXiv:2608.09421v1 Announce Type: cross Abstract: Wearable human activity recognition (HAR) remains challenging due to the computational and energy constraints of deep learning models on resource-limi

LLM-Driven AutoML for Cross-Lingual Handwritten OCR: Closed-Loop Neural Architecture Search with GPT-5, GPT-4o, and Claude Sonnet 4

arXiv:2607.15509v2 Announce Type: replace-cross Abstract: We present a fully automated closed-loop AutoML framework that uses GPT-5, GPT-4o, and Claude Sonnet 4 as autonomous neural architecture desig

Matryoshka Language Model Suites

arXiv:2608.09703v1 Announce Type: new Abstract: Training a language model suite classically requires training each model separately and serving them independently. We improve both training and inferen

Measuring the Wrong Thing: Internal Harmfulness Scores Anti-Rank Successful Jailbreaks

arXiv:2608.09624v1 Announce Type: cross Abstract: Internal safety scores judge a prompt before any text is generated, and they are validated by how well they separate harmful prompts from benign ones.

Mind the Hook: Source-Level Auditing of Privacy Defenses in Retrieval-Augmented Generation

arXiv:2608.09001v1 Announce Type: cross Abstract: Black-box privacy scores for retrieval-augmented generation (RAG) are difficult to interpret unless the audited defense's active pipeline hook is know

Mitigating Gender Bias in English to Romanian Machine Translation

arXiv:2608.08606v1 Announce Type: cross Abstract: Machine translation (MT) systems often fail to correctly translate gender, especially when converting from a gender-neutral language like English to a

Mitigating Over-Personalization in LLMs via Structured Memory

arXiv:2608.08300v1 Announce Type: new Abstract: Conversational assistants increasingly rely on persistent long-term memory to personalize responses across sessions. However, when stored user informati

Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models

arXiv:2608.09696v1 Announce Type: new Abstract: Predicting the answer to interventional ``what if'' questions --- the outcome of an action never taken --- requires a mechanistic, causal model, not a c

MoE-Prism: Disentangling Monolithic Experts for Elastic MoE Services via Model-System Co-Designs

arXiv:2510.19366v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) scales model capacity through sparse activation, and is becoming an important architecture for large language models (LLMs)

researcharxiv-cs-cl

Motif 3: Technical Report

arXiv:2608.09119v1 Announce Type: new Abstract: We introduce Motif 3, a decoder-only Mixture-of-Experts language model with 314 billion total parameters and 13.2 billion activated per token. Each spar

MRBench: A Comprehensive Benchmark for Human Motion-Text Retrieval

model-releasesarxiv-cs-cv

arXiv:2608.07993v1 Announce Type: new Abstract: Human motion-text retrieval provides a rigorous means of assessing cross-modal alignment. Prevailing benchmarks are dominated by homogeneous indoor moti

Agents

Multi-Task Consistency-based Detection of Adversarial Attacks

arXiv:2608.07750v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) have found successful deployment in numerous vision perception systems. However, their susceptibility to adversarial attac

agentsarxiv-cs-ai

Multimodal Skin Lesion Classification with Swin Transformer and Clinical Metadata Fusion

arXiv:2608.07574v1 Announce Type: new Abstract: Skin lesion classification plays an important role in supporting the early diagnosis of skin cancer. However, automated analysis remains challenging due

Not All Visual Tokens Are Equally Safe to Remove:Consequence-Sensitive Visual Token Compression

arXiv:2608.09176v1 Announce Type: cross Abstract: Visual token compression for vision--language models (VLMs) has largely relied on criteria such as attention, redundancy, and uncertainty to maximize

OD-Gear: Online Decomposition and Group Sampling for Expert-Guided Adversarial Routing in Scalable Capacitated Vehicle Routing

arXiv:2602.00488v3 Announce Type: replace Abstract: Solving large-scale capacitated vehicle routing problems (CVRP) is hindered by the high complexity of classical heuristics and the limited generaliz

safetyarxiv-cs-lg

Local Ai

On-Device Multi-Species Malaria Detection with Uncertainty-Calibrated Slide-Level Aggregation

arXiv:2608.08566v1 Announce Type: cross Abstract: Malaria remains a leading cause of mortality in resource-limited settings, where expert microscopists are scarce. Automated diagnosis based on microsc

local-aiarxiv-cs-ai

Opportunity Is Not Realizability: Selection-Valid Diagnostics for Multi-LLM Routing

arXiv:2608.08265v1 Announce Type: new Abstract: Oracle routing measures how much a pool of language models could gain from per-query selection, but the diagnostic has two flaws: testing against a best

researcharxiv-cs-lg

Overcoming Data Scarcity and Confidentiality in Hardware Assurance via Synthetic Generation

arXiv:2608.09914v1 Announce Type: cross Abstract: Hardware assurance relies on scanning electron microscopy (SEM) to verify nanoscale structures, but assembling the large, high-quality datasets requir

PAM: Training Policy-Aligned Moderation Filters at Scale

arXiv:2505.19766v4 Announce Type: replace Abstract: Large language models (LLMs) remain vulnerable to misalignment and jailbreaks, making external safeguards like moderation filters essential, yet exi

safetyarxiv-cs-cl

PolypSteer: Counterfactual Endoscopic Synthesis via Training-Free Activation Steering

arXiv:2603.07066v2 Announce Type: replace-cross Abstract: Generative diffusion models are increasingly used for medical imaging data augmentation, but text prompting cannot produce causal training dat

Population-Level Generative Modeling for Ranking Data

arXiv:2608.08422v1 Announce Type: cross Abstract: Ranking data arise in scientific and machine learning applications, including recommendation systems, information retrieval, voting, marketing, and AI

Position Bias in Ordinal Classification: A Systematic Evaluation

arXiv:2608.08869v1 Announce Type: new Abstract: Large language models are increasingly used for ordinal classification, yet semantically equivalent changes to prompt organization can alter their predi

safetyarxiv-cs-cl

Preserving Item Semantics for Free: Rethinking Token Initialization in LLM-Based Generative Recommendation

arXiv:2608.07816v1 Announce Type: cross Abstract: Recent advances in generative recommendation (GR) leverage large language models (LLMs) as recommender backbones, enabling LLMs to directly generate r

Probabilistic Circuits for Knowledge Graph Completion with Reduced Rule Sets

arXiv:2508.06706v2 Announce Type: replace Abstract: Rule-based methods for knowledge graph completion provide explainable results, but often require tens of thousands of rules to achieve competitive p

Applications

Progressive Learned Image Compression for Machine Perception

arXiv:2512.20070v2 Announce Type: replace Abstract: Recent advances in learned image codecs have extended from human perception toward machine perception However, progressive image compression with fi

applicationsarxiv-cs-cv

RAGMesh with FaME-G2E: Long-Form Text-Driven 3D Face Generation and Editing

model-releasesarxiv-cs-cv

arXiv:2608.09186v1 Announce Type: new Abstract: Text-driven 3D face generation and editing remains challenging due to the difficulty of translating long-form descriptions into fine-grained facial geom

Removing Infrastructure Barriers in Human-Robot Collaboration Through Wireless Reconfigurable Cells

arXiv:2608.09658v1 Announce Type: cross Abstract: Human-Robot Collaboration (HRC) plays a vital role in dynamic, high mix, low volume industrial scenarios such as remanufacturing, which frequently fac

safetyarxiv-cs-cv

Reproducing and Stress-Testing Two Approaches to LLM Reasoning Reliability: Test-Time Probability Aggregation and Logic-Representation Editing

arXiv:2608.08514v1 Announce Type: new Abstract: We independently reproduce two recent methods for making large language model (LLM) reasoning more reliable, and stress-test them across domains and mod

Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models

arXiv:2508.16406v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) remain vulnerable to jailbreak attacks, which attempt to elicit harmful responses from LLMs. The evolving nature

safetyarxiv-cs-cl

RL-Native Distillation: Exploiting Scored Trajectories for Few-Step Image Generation

arXiv:2608.09226v1 Announce Type: cross Abstract: Efficient text-to-image generation requires both reinforcement-learning (RL)-based reward alignment and few-step distillation, yet these procedures ar

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems

model-releasesarxiv-cs-cl

arXiv:2608.08237v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems in production operate under strict service level objectives (SLOs) on tail latency and infrastructure cos

SC^{2}-WM: A Self-Correcting World Model with Closed-Loop Feedback for Vision-and-Language Navigation in Continuous Environments

arXiv:2608.07548v1 Announce Type: cross Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to make fine-grained navigation decisions under partial observabili

ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB

arXiv:2608.07945v1 Announce Type: cross Abstract: Cloud-native serverless data warehouses achieve fine-grained elasticity by decoupling storage from compute, yet determining the optimal resource alloc

Scaling Audio Models Efficiently: A Joint Study of Compute Constraints and Optimization Behavior

arXiv:2606.22790v2 Announce Type: replace-cross Abstract: In this paper, we investigate the tradeoffs between compute allocation and model performance for two speech processing tasks: Automatic Speech

SegDem: Segmentation helps Demosaicing

arXiv:2608.07916v1 Announce Type: new Abstract: Image demosaicing reconstructs a full-color image from incomplete color measurements produced by a sensor covered with a color filter array (CFA). Most

Agents

Self-Evolving Neuro-Symbolic Skills for Tool-Augmented Spatial Reasoning

arXiv:2608.07955v1 Announce Type: new Abstract: Large vision-language models have achieved strong performance in multimodal reasoning, but they remain unreliable on fine-grained spatial tasks that dem

agentsarxiv-cs-ai

Shape Mutating Expert Compression:LorExperts and BTExperts

arXiv:2608.07814v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models deliver high capacity at low per-token compute, but deploying them cheaply requires compressing their many ex

SkillReason: Reasoning-Enhanced Agent Skill Retrieval for Implicit User Requests

arXiv:2608.08640v1 Announce Type: new Abstract: Large language model agents increasingly rely on reusable skills to extend their capabilities beyond parametric knowl- edge. However, retrieving the app

Local Ai

SLAP: Selective Local Vision-Language Alignment for Fish Re-Identification via Partial Optimal Transport

arXiv:2608.08840v1 Announce Type: new Abstract: Individual fish re-identification (ReID) is a fine-grained recognition problem in which identity-discriminative cues are often localized to specific bod

local-aiarxiv-cs-cv

SLIM-0.5B: Learning Action-Grounded Predictive Latents for Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.09771v1 Announce Type: new Abstract: Vision-language-action policies rely on large multimodal backbones to jointly perform perception, language conditioning, and action generation at every

SPECTRA: Pushing the KV Cache Beyond the 2-Bit Cliff via Spectral Transform Coding

arXiv:2608.07915v1 Announce Type: new Abstract: Large language models (LLMs) increasingly read long inputs in the agentic era, from whole documents and codebases to conversations across many turns. Th

SPRInG: Continual LLM Personalization via Selective Parametric Adaptation and Retrieval-Interpolated Generation

arXiv:2601.09974v2 Announce Type: replace Abstract: Personalizing Large Language Models typically relies on static retrieval or one-time adaptation, assuming user preferences remain invariant over tim

Local Ai

SRE-FER: Regional residual evidence learning for mitigating local evidence dilution in fine-grained facial expression recognition

arXiv:2608.08702v1 Announce Type: new Abstract: Fine-grained facial expression recognition (FER) hinges on capturing subtle muscular cues that distinguish adjacent emotions. Yet capturing these cues p

local-aiarxiv-cs-cv

Staying True to the Origin: Continuous Image Stylization with Smooth Transitions

model-releasesarxiv-cs-cv

arXiv:2608.08125v1 Announce Type: new Abstract: Recent advances in generative models have achieved remarkable performance in text- and image-conditioned editing. However, preserving the content of a g

Structured Phonological Representations for Audio-Articulatory rtMRI Speech Classification

arXiv:2608.09767v1 Announce Type: new Abstract: Real-time MRI makes it possible to observe vocal-tract articulation during speech, but mapping these articulatory patterns to phonetic and phonological

researcharxiv-cs-cl

TAMS: Task-Aware Multi-View Adaptive Streaming for Wireless Telerobotic Manipulation

arXiv:2608.09731v1 Announce Type: new Abstract: Wireless telerobotic manipulation relies on timely multi-view video feedback, but the available uplink bandwidth is often limited and dynamic. This pape

researcharxiv-cs-ro