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HalluScope: Fine-grained Hallucination Diagnosis for Multimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2607.21105v1 Announce Type: new Abstract: Although Multimodal Large Language Models have achieved strong performance across a wide range of vision-language tasks, they still suffer from hallucin

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Research

HAMON: Passive Optical Sequence Mixing for Long-Horizon Forecasting

DGX agent

arXiv:2606.17028v2 Announce Type: replace-cross Abstract: Simple linear and frequency-domain models remain surprisingly competitive in long-horizon time-series forecasting, and recent mechanistic evid

researcharxiv-cs-ai

24 Jul 2026

Local Ai

Hardware-Software Co-Design for Float16 On-Device Training on RISC-V Single-Core

arXiv:2607.21130v1 Announce Type: cross Abstract: By leveraging standard RISC-V extensions, namely Zfh (scalar float16) and Zvfh (vector float16), this work proposes an open-source framework to enable

local-aiarxiv-cs-ai

HARP: The Human--AI Research Platform

arXiv:2607.20773v1 Announce Type: cross Abstract: Large language models (LLMs) have shifted human--computer interaction from `traditional'' interface journeys toward more conversational exchanges. Res

agentsarxiv-cs-ai

HERMES: Heterogeneous Edge-Relational Multi-Head Embedded SSM Attention for Traffic Conflict Prediction at Signalized Intersections

arXiv:2607.20505v1 Announce Type: cross Abstract: Surrogate safety measures (SSMs) enable proactive traffic safety assessment, but many existing methods evaluate pairwise interactions independently or

safetyarxiv-cs-lg

HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors

arXiv:2607.21281v1 Announce Type: new Abstract: Topological maps are key outputs of autonomous driving perception systems, delivering essential road information for path planning. They identify instan

agentsarxiv-cs-cv

HierarchicalDAEW: Domain-Aware Edge-Weighted Graph Convolution with Evidential Uncertainty for Multi-Section Spatial Gene Expression Prediction from H&E Histology

arXiv:2607.20896v1 Announce Type: new Abstract: Spatial transcriptomics assays remain costly and technically demanding, restricting transcriptome-wide profiling to specialist settings and preventing r

researcharxiv-cs-lg

Hilbert Operator for Progressive Encoding (HOPE): A Mathematical Framework for Deconstructing Learned Representations in Deep Networks

arXiv:2607.21366v1 Announce Type: cross Abstract: Deep neural networks encode complex representations, but deconstructing this internal knowledge remains a challenge. Given the link between learning a

HiMe: Real-Time Self-Hosted Personal Agent Platform for Health Insights with Wearable Devices

arXiv:2607.21019v1 Announce Type: new Abstract: Traditional approaches to wearable health signal analysis, such as smartwatches, are constrained by rigid analytical frameworks and limited personalisat

agentsarxiv-cs-ai

How Many Bits Can an Adapter Write? Measuring the Capacity and Memorization of Parameter-Efficient Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2607.21351v1 Announce Type: new Abstract: A LoRA adapter is a few megabytes that almost everyone treats as a skill rather than a record of the data behind it. We put that assumption on a scale.

How Rules Represent Causal Knowledge: Causal Modeling with Probabilistic Logic Programming

arXiv:2607.21208v1 Announce Type: new Abstract: Pearl famously argues that causal knowledge enables the prediction of intervention effects. By contrast, purely descriptive knowledge supports only conc

Human-in-the-Loop Large Language Model Framework for Identification of Cutaneous Immune-Related Adverse Events

arXiv:2607.20428v1 Announce Type: new Abstract: This study evaluated a retrieval-augmented, multi-agent large language model (LLM)-driven, human-in-the-loop framework for detecting cutaneous immune-re

agentsarxiv-cs-cl

Human-Inspired Framework for Robotic Craniotomy: Integrating Multimodal Fusion and Adaptive Trajectory Adjustment

arXiv:2607.21058v1 Announce Type: new Abstract: Manual craniotomy is a high-risk, skill-dependent procedure associated with surgeon fatigue and potential dural injury. While robotic approaches have im

safetyarxiv-cs-ro

Hybrid MKNF with Classical Negation in the Rule Component

arXiv:2607.21202v1 Announce Type: cross Abstract: Hybrid MKNF knowledge bases under the well-founded semantics integrate Description Logics with Logic Programming. However, they do not support classic

safetyarxiv-cs-ai

HyperImageNet: A Large-Scale High-Spatial Resolution Hyperspectral Imagery Classification Benchmark

model-releasesarxiv-cs-cv

arXiv:2607.21050v1 Announce Type: new Abstract: We present HyperImageNet, a large-scale benchmark for fine-grained hyperspectral land-cover understanding. The dataset contains 26,084 airborne hyperspe

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws

arXiv:2607.20541v1 Announce Type: cross Abstract: We introduce HypNO, a graph-based neural operator for scalar hyperbolic conservation laws. HypNO operates directly on a space-time graph of finite-vol

HyWorldVLA: A Vision-Language-Action Model with Hybrid World Modeling for Autonomous Driving

arXiv:2607.20988v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models augmented with world modeling represent a promising paradigm for end-to-end autonomous driving. While pixel-level

i2Nav-Robot: A Large-Scale Indoor-Outdoor Robot Dataset for Multi-Sensor Fusion Navigation

arXiv:2508.11485v3 Announce Type: replace Abstract: Accurate and reliable navigation is crucial for autonomous unmanned ground vehicles (UGVs). However, current UGV datasets fall short in meeting the

agentsarxiv-cs-ro

ICAE-Bench: Evaluating Coding Agents as Interactive Project Builders

arXiv:2607.21217v1 Announce Type: new Abstract: The recent emergence of vibe-coding workflows is changing what coding agents are expected to do. Instead of merely completing code under fully specified

Identifying Good Rules for Efficient SAT Encodings of Single-Constant Multiplication Using Machine Learning

arXiv:2607.21188v1 Announce Type: new Abstract: The Single Constant Multiplication problem is a fundamental NP-hard optimization task in hardware design, which seeks to decompose a fixed constant usin

ImplicitBBQ: Benchmarking Implicit Bias in Large Language Models through Characteristic Based Cues

arXiv:2604.01925v2 Announce Type: replace-cross Abstract: Large Language Models increasingly suppress biased outputs when demographic identity is stated explicitly, yet may still exhibit implicit bias

Improved lower bounds for the Shannon capacity of odd cycles

arXiv:2607.21517v1 Announce Type: cross Abstract: The Shannon capacity Theta(G) of a graph G quantifies the maximum rate at which information can be transmitted with zero error over a noisy channel. I

Applications

Improving Access to Essential Medicines via Decision-Aware Machine Learning

arXiv:2607.20542v1 Announce Type: cross Abstract: A critical challenge in healthcare systems in low- and middle-income countries (LMICs) is the efficient and equitable allocation of scarce resources,

applicationsarxiv-cs-ai

Incomplete Prompt Jailbreaks in Large Language Models

arXiv:2607.20473v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly released as open-weight models with safeguards against harmful requests. Nevertheless, sentence completion

Incremental Optimal Assignment for Real-Time Crowd Tracking

arXiv:2607.21368v1 Announce Type: new Abstract: Multi-object tracking in dense crowds requires solving a bipartite assignment problem between detections and trajectories at every video frame. The clas

researcharxiv-cs-cv

Inducing Comparability of Factorised Probability Distributions

arXiv:2607.20502v1 Announce Type: new Abstract: To allow for principled comparison between two probabilistic graphical models defined over non-identical variable sets, they have to be lifted to a comm

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning

arXiv:2607.21591v1 Announce Type: new Abstract: Diffusion and flow-matching models dominate conditional image generation, yet inference-time scaling for these models is far less developed than for aut

safetyarxiv-cs-cv

InferenceBench: A Benchmark for Open-Ended LLM Inference Optimization by AI Agents

arXiv:2607.20468v1 Announce Type: new Abstract: AI agents are increasingly used to automate research and development tasks, yet existing benchmarks typically evaluate them on prescribed workflows or n

Local Ai

Information-Theoretically Secure Aggregation for Lightweight Federated Learning: Resilient to Dropouts and Adversaries

arXiv:2607.20890v1 Announce Type: new Abstract: On-device federated learning (FL) enables privacy-preserving and personalized model training on resource-constrained devices such as smartphones and IoT

local-aiarxiv-cs-lg

Instruct-FD: Can Your Full-Duplex Speech System Follow Turn-Taking Instructions?

arXiv:2607.20460v1 Announce Type: cross Abstract: Current full-duplex (FD) spoken dialogue systems can produce fluid interactions, yet it remains unclear whether they can adapt their turn-taking behav

Interaction Dynamics Modeling and Predictive Control for Safe Steerable Catheter--Tissue Interaction

arXiv:2607.20939v1 Announce Type: cross Abstract: Safe steerable catheter control is fundamentally a problem of interaction dynamics: the tip must follow a planned motion, remain compliant against mov

safetyarxiv-cs-ai

Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit

arXiv:2512.10092v2 Announce Type: replace Abstract: Analyzing large-scale text corpora is a core challenge in machine learning, crucial for tasks like identifying undesirable model behaviors or biases

Is Deep Research Reliable? Misleading Knowledge Induces False Conclusions

arXiv:2607.20891v1 Announce Type: new Abstract: Deep Research agents extend LLM-based assistants into long-horizon workflows involving planning, retrieval, evidence synthesis, and report generation, y

Is MoE Routing a Huffman Code? Discovering the Frequency-Diversity Law in Chain-of-Thought

arXiv:2607.20427v1 Announce Type: cross Abstract: Mixture-of-Experts architectures have revolutionized scaling, yet the underlying logic of their routing remains a black box. In this paper, we uncover

Is Your Safe Controller Actually Safe? A Critical Review of CBF Tautologies and Hidden Assumptions

arXiv:2603.06954v2 Announce Type: replace Abstract: This tutorial provides a critical review of the practical application of Control Barrier Functions (CBFs) in robotic safety. While the theoretical f

safetyarxiv-cs-ro

Isolating LLM Alignment from Regex: Zero Coverage and Metric-Dependent Divergence Under Adversarial Mutation

arXiv:2607.20494v1 Announce Type: new Abstract: Production LLM applications commonly stack a regex filter in front of model-side alignment; prior work found no measurable coverage gain from adding a l

IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests

arXiv:2607.20759v1 Announce Type: cross Abstract: AI coding agents powered by LLMs are increasingly integrated into real-world software development, where they generate, edit, and execute code with au

JAXBench: Benchmarking Autonomous TPU Kernel Optimization

arXiv:2607.20466v1 Announce Type: new Abstract: Rigorous benchmarks have driven progress in autonomous GPU kernel performance optimization by establishing a shared target to hillclimb on, but no equiv

Applications

Joint Utilization of Geospatial and census proxies for Autoencoder-Assisted Downscaling (JUGAAD) of socioeconomic indicators in India

arXiv:2607.20559v1 Announce Type: cross Abstract: Monitoring poverty and food security indicators is imperative for addressing socioeconomic challenges in developing nations. A limitation is mismatche

applicationsarxiv-cs-ai

KeySI: An Interaction Framework for Tuning Text Embeddings Based on Human Feedback

arXiv:2607.20556v1 Announce Type: new Abstract: In large-scale text analysis tasks, pre-trained language models are often used to embed text corpora for downstream analysis. However, such models may s

safetyarxiv-cs-ai

Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations

arXiv:2607.20426v1 Announce Type: cross Abstract: Existing LLM hallucination mitigation methods, including prompt engineering and model optimization, either hardly alter models'internal knowledge or h

Hardware

KroQuant: Kronecker-Structured Block Transforms for Efficient Post-Training Quantization of Diffusion Transformers

arXiv:2607.21446v1 Announce Type: cross Abstract: Post-training quantization (PTQ) of diffusion transformers (DiTs) to W4A4 severely degrades output quality, because activations entering each linear l

hardwarearxiv-cs-cv

Latent Variable-Mediated Cross-Learning for Few-Shot Acoustic Impedance Imaging

arXiv:2607.20989v1 Announce Type: new Abstract: Acoustic impedance imaging is a fundamental yet severely ill-posed problem in subsurface analysis: the seismic wavelet is unknown, observations are band

researcharxiv-cs-cv

Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing

model-releasesarxiv-cs-lg

arXiv:2607.20723v1 Announce Type: cross Abstract: This work presents LeakyLMs, a set of attacks that leak proprietary model, architecture, and deployment information from production language models. L

LeanFlow: A Case Study in Workflow-Driven Lean Autoformalization

arXiv:2607.20503v1 Announce Type: new Abstract: We present and evaluate LeanFlow, an LLM agent system specialized for translating mathematical papers into buildable Lean projects. Recent verifier-in-t

agentsarxiv-cs-ai

Learn2Zinc: Fine-tuning Small Language Models for Text-to-Model Translation in MiniZinc

arXiv:2607.20456v1 Announce Type: cross Abstract: Large language models excel at code generation for mainstream programming languages but struggle with rare, domain-specific languages such as MiniZinc

Learning-based Seam Correspondence Reconstruction in Sewing Patterns

arXiv:2607.21213v1 Announce Type: new Abstract: Digital sewing patterns typically consist of disjoint 2D panels without explicit stitch annotations, making downstream 3D modeling reliant on labor-inte

researcharxiv-cs-cv

Applications

Learning to Detect UI Principle Violations via Reinforcement Learning

arXiv:2607.20690v1 Announce Type: new Abstract: Small language models and coding agents increasingly generate web front-end code, yet their outputs are typically evaluated primarily for functional cor

applicationsarxiv-cs-cl