Search: “inference”

Temporal Multi-Signal Fusion for Token-Level Hallucination Detection

arXiv:2608.18115v1 Announce Type: cross Abstract: Token-level hallucination detectors score each token independently from a single signal, and fail exactly when the generating model is confidently wro

Hardware

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TokenPowerSandbox: Evidence-Gated CPU-First Screening for Energy-Aware LLM Serving

DGX agent

arXiv:2608.18149v1 Announce Type: cross Abstract: Energy-aware LLM serving requires comparing configurations under realistic request shapes, yet exhaustive target-GPU profiling is costly and a cheap p

hardwarearxiv-cs-ai

20 Aug 2026

Training Chemical Plausibility-Aware Large Language Models for Single-Step Retrosynthesis

arXiv:2608.18940v1 Announce Type: cross Abstract: Single-step retrosynthesis is a central component of computer-aided synthesis planning, yet its intrinsically one-to-many nature is poorly captured by

Applications

Transportable Causal Effect Estimation across Networks under Interference

arXiv:2608.18932v1 Announce Type: new Abstract: Estimating causal effects under network interference typically assumes that the network used for training and the network used for deployment coincide.

applicationsarxiv-cs-lg

UMER: Unifying Embedding and Ranking via Pair-Aware Discriminative Reasoning for Universal Multimodal Retrieval

arXiv:2608.18504v1 Announce Type: new Abstract: Universal multimodal retrieval aims to support diverse instruction-aware retrieval tasks, demanding both efficient corpus-scale matching and fine-graine

Vector Symbolic Policy Gradient

arXiv:2608.18404v1 Announce Type: cross Abstract: We answer this question with Vector-Symbolic Policy Gradient (VSPG), a discrete-action actor that represents each action by a unit-norm hypervector an

What is Missing from AI Post-Training AI: An Empirical Analysis

arXiv:2608.19072v1 Announce Type: new Abstract: Large language model (LLM) agents can now post-train an LLM end-to-end. They can write code, launch training, evaluate checkpoints, and improve downstre

When Clean Signals Are Not Enough: Detecting Structural Ambiguity for Safe Wearable Stress Classification

arXiv:2608.18397v1 Announce Type: new Abstract: Wearable stress classifiers can achieve strong average performance while failing completely for a particular individual. On WESAD, a Random Forest reach

When Do LLMs Actually Help? Evaluating LLMs as Data Quality Annotators

arXiv:2608.18158v1 Announce Type: cross Abstract: LLMs have been increasingly used to catch data quality issues automatically, but we know very little about how consistent these judgments actually are

Which Negatives Matter? Ask Your Text Encoder: Adaptive Similarity Margins for Dense-Caption Retrieval

arXiv:2608.18521v1 Announce Type: new Abstract: Dense-caption retrieval has recently been improved by introducing segmentation, edge maps, LLM-filtered captions, and cross-modal modules into contrasti

Abra: Scaling Diffusion Image Training

model-releasesarxiv-cs-lg

arXiv:2608.17286v1 Announce Type: new Abstract: Compute-optimal scaling laws guide the training of frontier language models yet remain largely unexplored for visual generation. We present a systematic

Advancing Health Equity through Multi-Level Fairness in Health Informatics

arXiv:2608.16902v1 Announce Type: cross Abstract: The increasing integration of machine learning in healthcare has highlighted critical challenges related to fairness, transparency, and health equity.

safetyarxiv-cs-lg

Agentic ESOpt: Fine-Tuning Long-Horizon LLM Agents with Minimal GPU Requirements

model-releasesarxiv-cs-lg

arXiv:2608.17310v1 Announce Type: new Abstract: Reinforcement Learning (RL) has been promising in single-turn LLM fine-tuning. However, long-horizon agentic reasoning introduces increasingly branching

ArguLens: An Open-Source System for Automated Essay Scoring and Label-Aware Feedback Generation

model-releasesarxiv-cs-cl

arXiv:2608.17356v1 Announce Type: new Abstract: Most automated essay scoring (AES) systems output a single holistic score without interpretable evidence and rely on closed APIs that introduce data pri

BayesPrompt: human readable prompts that make sense

arXiv:2608.17866v1 Announce Type: new Abstract: Reconstructing prompts that can elicit a desired answer or behaviour in an LLM is an open and important research topic. Optimisation methods which aim a

researcharxiv-cs-cl

Hardware

Beyond FLOPs: Energy-Aware Knowledge Distillation for Sustainable LLMs on Code-Related Task

arXiv:2608.17515v1 Announce Type: cross Abstract: Background: Large Language Models (LLMs) are increasingly being applied to Software Engineering (SE) tasks, achieving high accuracy across problems su

hardwarearxiv-cs-ai

Beyond the Trace: Coupling an Interpretable Reasoning-State Readout to Native MoE Routing

arXiv:2608.17638v1 Announce Type: new Abstract: What a reasoning model writes is only a partial record of the process that produces it. We introduce a two-level internal readout for mixture-of-experts

BrainNorm: A Foundation Model that knows Normal via Semantic Atlas Pretraining

arXiv:2608.17521v1 Announce Type: new Abstract: We introduce BrainNorm, a normative foundation model, trained and tested on ~66,000 T1-weighted structural MRI (T1w sMRI) scans. By leveraging language-

Can Large Language Models Explain Flight Safety Events? A Prior-Guided Semantic LLM-based Approach

arXiv:2608.18017v1 Announce Type: new Abstract: Improving flight safety with flight data requires not only accurate detection of risk events, but more importantly, clear interpretation of their underl

Cascaded Multi-Scale Attention for Enhanced Multi-Scale Feature Extraction and Interaction with Low-Resolution Images

arXiv:2412.02197v5 Announce Type: replace Abstract: In real-world applications of image recognition tasks, such as human pose estimation, cameras often capture objects, like human bodies, at low resol

ChatPlanner: A Large Language Model Framework for Personalized Public Transit Routing

arXiv:2606.15315v2 Announce Type: replace Abstract: Personalized public transit routing in public transit systems remains challenging due to the difficulty of capturing and integrating diverse user pr

CHM-Net: Center Heatmap-driven Macro-Micro Modeling Network for MRI-based Microbial Density Stratification

arXiv:2607.09812v2 Announce Type: replace-cross Abstract: Microbial density is clinically important for tumor assessment and treatment decision-making, and recent advances in deep learning suggest tha

CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning

model-releasesarxiv-cs-cv

arXiv:2507.09471v2 Announce Type: replace Abstract: Continual Learning (CL) empowers AI models to continuously learn from sequential task streams. Recently, parameter-efficient fine-tuning (PEFT)-base

COMIC: Reference-Aware Safety Gating for Multimodal Large Language Models

arXiv:2608.17234v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used to interact with screenshots, scanned documents, diagrams, and other visually grounded

Counterfactual Anatomy-guided Spatial-Temporal Decoding for Annotation-Free Hallucination Mitigation in Medical VLMs

arXiv:2608.17427v1 Announce Type: new Abstract: Medical vision-language models (Med-VLMs) have demonstrated strong performance on medical visual question answering, yet they remain prone to hallucinat

Cross-Model Memory Transfer via Target-Side Reader Adaptation

arXiv:2608.17050v1 Announce Type: cross Abstract: Methods for improving knowledge use in large language models typically fall into two regimes. Non-parametric retrieval offers flexible access to exter

Diagonal Multi-omics Integration of Heterogenous Datasets

arXiv:2608.16968v1 Announce Type: cross Abstract: In this paper, we consider methods for the diagonal multi-omics integration of heterogeneous datasets. Several approaches to the nature of biological

researcharxiv-cs-lg

DiSCO: Defending text-to-image generation through distribution-guided contrastive prompt optimization

arXiv:2608.17067v1 Announce Type: new Abstract: As text-to-image generative models advance, they raise critical safety concerns, particularly the generation of Not-Safe-For-Work (NSFW) content such as

ETHEREAL: A 25.6-mus/inf. Low-latency Event-driven Graph-neural-network Processor for High-resolution Vision at the Edge

arXiv:2608.17787v1 Announce Type: cross Abstract: Dynamic vision sensors (DVS) are enticing candidates to reach the low-latency, sub-ms target of edge-vision applications, as they generate events with

Exploring Efficient Open-Vocabulary Segmentation in the Remote Sensing

arXiv:2509.12040v3 Announce Type: replace-cross Abstract: Open-Vocabulary Remote Sensing Image Segmentation (OVRSIS), an emerging task that adapts Open-Vocabulary Segmentation (OVS) to the remote sens

Force-Based Offset Estimation for Keyed Peg-in-Hole Assembly Using Local Gaussian Process Regression

arXiv:2608.17691v1 Announce Type: new Abstract: Key-keyway assembly tasks impose strict geometric constraints and are highly sensitive to grasp pose deviations in uncertain environments. This work pre

local-aiarxiv-cs-ro

GeoWeaver: Accurate Long-Sequence 3D Reconstruction via Hierarchical Geometric Assembly

arXiv:2608.17389v1 Announce Type: new Abstract: Long-sequence 3D reconstruction from RGB videos requires both accurate local geometry and globally consistent camera motion. Feed-forward models provide

GS-Voxel: Fitting-Free Structured Latents for Large-Scale 3DGS Generation

arXiv:2608.17988v1 Announce Type: new Abstract: Many scalable latent 3D generators operate on structured tensors, whereas pre-optimized 3D Gaussian Splatting (3DGS) reconstructions are unordered, spat

HLSR: Hybrid Live Forecast Selective Dynamic Vehicle Rerouting for Real-Time Congestion Avoidance

arXiv:2608.18056v1 Announce Type: new Abstract: Urban traffic congestion reduces productivity and increases travel cost and emissions. Network-wide live travel-time shortest-path rerouting can be high

Hardware

Jetson-ORB-SLAM3: Accuracy-Preserving GPU Implementation for Edge Computing Devices

arXiv:2608.17874v1 Announce Type: new Abstract: Visual-inertial SLAM on low-power edge platforms is constrained by the cost of dense feature extraction and loop closure. Prior GPU ports of ORB-SLAM tr

hardwarearxiv-cs-ro

Language Has Two Parameters: Narrative-Induced Semantic Plasticity and Phase-Sensitive Interpretation

model-releasesarxiv-cs-cl

arXiv:2608.18041v1 Announce Type: new Abstract: Language has two parameters. Count how often words occur together and you estimate amplitude, the strength of association. Word embeddings and attention

LEGO-RL: Harness-Native Reinforcement Learning for Coding Agents

arXiv:2608.17393v1 Announce Type: new Abstract: Reinforcement learning for coding agents increasingly relies on long-running agent harnesses to manage tool integration, repository contexts, and execut

Tutorials

Live Interactive Training for Video Segmentation

arXiv:2603.26929v2 Announce Type: replace Abstract: Interactive video segmentation often requires many user interventions for robust performance in challenging scenarios (e.g., occlusions, object sepa

tutorialsarxiv-cs-cv

LLM-Derived Preference Judgments Are Not Self-Consistent

arXiv:2608.17644v1 Announce Type: new Abstract: Agents increasingly interpret a person's natural-language preferences by querying an LLM for numerical preference judgments, e.g., by asking how much th

LLMs for Medical Consultation Are Evaluated Too Late: The Preformulation Gap

arXiv:2608.17330v1 Announce Type: new Abstract: Large language models for medical consultation are often evaluated after a clinical problem has already been made clear, although real consultations may

Tutorials

MemCatalyst: Amplifying Data Auditing on Vision-Language Models via Data Poisoning

arXiv:2608.17722v1 Announce Type: cross Abstract: Vision-Language models (VLMs) achieve outstanding performance largely due to the amount of training data available on the internet. At the same time,

tutorialsarxiv-cs-lg

Memory Tree Guided Key Frame Querying for Efficient 3D Question Answering

arXiv:2608.18009v1 Announce Type: new Abstract: Answering questions accurately and efficiently in embodied scenarios presents significant challenges due to limited computational and memory resources f

MotoSafety: Edge-AI with Learned Temporal Importance for Two-Wheeler Collision Risk Assessment Under Time Pressure

arXiv:2608.17823v1 Announce Type: cross Abstract: Powered two-wheeler riders face critical safety challenges in low- and middle-income countries, yet limited studies exist on how cognitive stressors s

local-aiarxiv-cs-ai

MS-MFAD : Multimodal large language models for Face Anti-spoofing Detection

model-releasesarxiv-cs-cv

arXiv:2608.17328v1 Announce Type: new Abstract: Facial biometric recognition systems currently face compound threats intertwining generative AI and high-fidelity physical spoofing. Existing defenses s

No Gaussian Required: Contrastive Inverse Dynamics for JEPA World Models

arXiv:2608.17542v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn world models by predicting future embeddings, but the objective admits a trivial solution of a

Noisy group neurons with synchronous resetting for high-performance spiking neural networks

arXiv:2608.17394v1 Announce Type: new Abstract: Spiking neural networks (SNNs), characterized by bio-inspired neuronal dynamics and event-driven communication, have attained significant progress in re

Optimize Your Sampling: Tuned Diffusion Sampling with Bayesian Optimization

arXiv:2608.18040v1 Announce Type: cross Abstract: Sampling from a diffusion model typically requires many forward passes through a large neural network, making generation computationally expensive. Wh

ORViT-DR: Ordinally-Robust Hybrid ViT for Low-Resolution Diabetic Retinopathy Grading

model-releasesarxiv-cs-cv

arXiv:2608.16958v1 Announce Type: cross Abstract: Diabetic retinopathy (DR) is one of the main causes of impaired vision. A good and reliable automated grading system can make the screening process sa