Search: “model-releases”

Grounding Robot Generalization in Training Data via Retrieval-Augmented VLMs

model-releasesarxiv-cs-ro

arXiv:2603.11426v3 Announce Type: replace Abstract: Recent work on robot manipulation has advanced policy generalization to novel scenarios. However, it is often difficult to characterize how differen

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Model Releases

Handoff-H1: An Orchestrated Vision-Agent System for Material Quantity Takeoff from Construction Blueprints

DGX agent

arXiv:2608.15032v1 Announce Type: cross Abstract: Converting a set of architectural blueprints into a complete material quantity takeoff requires visual perception across drawing sheets, dimensional a

model-releasesarxiv-cs-ai

18 Aug 2026

HarmProfile: Characterizing Harmful Distributions in Frontier LLMs

arXiv:2608.14577v1 Announce Type: cross Abstract: Frontier large language models (LLMs) safety evaluation has largely treated harmful generation as an attack outcome rather than as an object of analys

Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents

arXiv:2608.15008v1 Announce Type: new Abstract: Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely th

HarnessEval-W: Agentifying the Evaluation of Visual Worlds

arXiv:2608.16859v1 Announce Type: new Abstract: A benchmark should deliver more than a scalar score: what makes an evaluation trustworthy is the reasoning that justifies the score. This is especially

Helios 2.0: A Robust, Ultra-Low Power Gesture Recognition System Optimised for Event-Sensor based Wearables

arXiv:2503.07825v3 Announce Type: replace-cross Abstract: We present an advance in wearable technology: a mobile-optimized, real-time, ultra-low-power event camera system that enables natural hand ges

HiPHI: A Large-Scale Benchmark for High-Precision Human Motion and Object-Interaction

arXiv:2608.16222v1 Announce Type: cross Abstract: Humanoid intelligence requires learning over an extremely diverse space of whole-body motions and physically grounded interactions. However, existing

Historical Backtesting for Scientific Question Discovery: A Protocol and Astronomy Pilot

arXiv:2608.16795v1 Announce Type: cross Abstract: Systems that generate scientific research questions are evaluated today by expert scores, LLM-as-judge ratings, or curated case studies -- all subject

HLE-Verified: A Systematic Verification and Structured Revision of Humanity's Last Exam

arXiv:2602.13964v4 Announce Type: replace Abstract: Humanity's Last Exam (HLE) has become a widely used benchmark for evaluating frontier large language models on challenging, multi-domain questions.

Hoeffding adaptive splitting trees for data stream classification with concept drift and ensemble learning

arXiv:2608.16659v1 Announce Type: cross Abstract: Ensembles of decision trees are well-established methods for data stream classification. In ensemble learning, Hoeffding Trees are widely adopted as b

Honeyquest for LLMs: Rethinking Cyber Deception for AI Attackers

arXiv:2606.21037v2 Announce Type: replace-cross Abstract: The empirical foundation of cyber deception relies on human-centered hypotheses, but the rapid emergence of autonomous, AI-enabled attackers c

How Many Samples Are Needed to Determine Causal Direction? Sharp Minimax Bounds for Bivariate LiNGAM

arXiv:2608.15840v1 Announce Type: cross Abstract: We study how many observations are needed to determine the causal direction between two linearly related variables. Classical LiNGAM theory shows that

How Sampling Strategy Affects Imbalance Mitigation in LiDAR Segmentation: A Study of Structured vs. Random Point-Based Architectures

arXiv:2608.16673v1 Announce Type: new Abstract: Class imbalance in LiDAR point clouds poses challenges for semantic segmentation in autonomous navigation and urban mapping. While 2D vision has numerou

HP2-SLAM: Adaptive Hybrid ICP for Robust and Efficient LiDAR SLAM

model-releasesarxiv-cs-ro

arXiv:2608.14996v1 Announce Type: new Abstract: Achieving robustness, accuracy, and efficiency simultaneously remains a central challenge in light detection and ranging (LiDAR) simultaneous localizati

Hybrid quantum recurrent neural network for remaining useful life prediction of turbofan engines

arXiv:2504.20823v3 Announce Type: replace Abstract: Accurate remaining useful life (RUL) estimation underpins safe operation and cost-effective maintenance of aerospace propulsion systems. We propose

HyMem: Hierarchical Context Management for Long-Horizon Agents via Information Isolation

arXiv:2608.15703v1 Announce Type: new Abstract: Large language model (LLM) agents often perform poorly on complex, long-horizon tasks because their context becomes increasingly cluttered over time. As

Identifying parameter couplings and uncertainties of mixed-noise stochastic systems via full-covariance Gaussian mixture network

arXiv:2608.15198v1 Announce Type: cross Abstract: Parameter identification of stochastic dynamical systems driven by mixed noises is challenging due to intractable likelihood functions. We propose PEN

iFuzz-Meta: An Interpretable Fuzzy Learning Framework Bridging Top-Down and Bottom-Up Knowledge Integration

arXiv:2608.14646v1 Announce Type: cross Abstract: Interpretable representation learning remains a key challenge in modern neural computation, particularly when models are expected not only to perform

Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities

arXiv:2501.12147v2 Announce Type: replace-cross Abstract: Selecting appropriate training data is crucial for instruction fine-tuning of large language models (LLMs), which aims to (1) elicit strong ca

Incoherent by Design? On the Moral Self-Consistency of LLMs

arXiv:2608.15354v1 Announce Type: new Abstract: LLMs are increasingly used in morally sensitive contexts, yet it is unclear whether they apply ethical principles consistently across situations. A mode

IndicQE-APE: A Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages

arXiv:2608.16344v1 Announce Type: new Abstract: Indic quality estimation (QE) and automatic post-editing (APE) data is spread across separate releases, so no single resource supports training and eval

Information Geometry of Message Passing

arXiv:2608.15922v1 Announce Type: cross Abstract: We show that the natural-gradient stationary condition of variational inference has an edge-local form on a Forney-style factor graph. We start from t

Informative Perturbation Selection for Uncertainty-Aware Post-hoc Explanations

arXiv:2603.14894v3 Announce Type: replace-cross Abstract: Trust and ethical concerns due to the widespread deployment of opaque machine learning (ML) models motivating the need for reliable model expl

INSPIRE: A Benchmark for Instruction-Aware Speech Retrieval

arXiv:2608.16203v1 Announce Type: cross Abstract: Existing speech retrieval systems rely on fixed similarity matching and cannot adapt to diverse user intents. We introduce INSPIRE, the first benchmar

Intelligent Base Station Deployment in Urban Wireless Networks: A Geographic Data-Informed Digital Twin Approach

arXiv:2608.14599v1 Announce Type: cross Abstract: The placement of base station (BS) is a fundamental determinant of coverage and capacity of urban wireless networks. Yet large-scale BS deployment opt

Interpretable Cross-Lingual Alignment in Small Language Models: Probing Cultural and Pragmatic Reasoning in Japanese-English Bilingual LLMs

arXiv:2608.14896v1 Announce Type: new Abstract: Large language models work well on English and behave in poorly understood ways on languages typologically far from it. Japanese is a clean example, whe

Iterative Refinement Diffusion for Super-Resolved Data Assimilation of Multiscale Physical Systems

arXiv:2608.14744v1 Announce Type: new Abstract: Recovering high-resolution states from sparse, low-resolution observations is a central challenge in scientific machine learning and data assimilation.

JailbreakSkill: Scaling Automated Red-Teaming with Reusable and Ever-Evolving Skills

arXiv:2608.16465v1 Announce Type: new Abstract: Automated red-teaming has produced a growing collection of attack strategies, yet they typically remain scattered across prompts and workflows, making t

KeyID: Decoupled Drafting and Keyframe Editing for Identity-Preserving Video Generation

arXiv:2608.16154v1 Announce Type: new Abstract: Identity-preserving video generation (IPVG) requires synthesizing videos that are faithful to both reference subjects and text prompts. Existing methods

Kozuchi Agent: A Language-Agnostic Open-Weight Agent for Software Repair

arXiv:2608.15579v1 Announce Type: cross Abstract: Industrial software-engineering teams increasingly need LLM agents that turn bug reports into correct patches, yet benchmark-scale operation adds long

L3Cube-IndicQuest v2: A Large-Scale Multilingual Benchmark for Evaluating Factual Knowledge of Large Language Models Across Indic Languages

arXiv:2608.15535v1 Announce Type: new Abstract: We present L3Cube-IndicQuest v2, a large-scale gold-standard multilingual question-answering benchmark for evaluating the India-specific factual knowled

Language Models that Think, Chat Better

arXiv:2509.20357v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) trains language models to use long chain-of-thought reasoning (CoT) in domains like mathematic

Large Language Models and their Awareness of Mechanics and Spatial Geometry

arXiv:2608.14615v1 Announce Type: new Abstract: Large Language Models (LLMs) perform well on established code-generation and mathematical-reasoning benchmarks, but their capabilities in mechanics and

Large Language Models Show Metacognitive Sensitivity in Medical Reasoning

arXiv:2608.14552v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated and used in medicine, but clinical usefulness depends on answer accuracy and whether confidence

LAVA: Logic-Aware Validation and Augmentation Framework for Large-Scale Financial Document Auditing

arXiv:2608.16763v1 Announce Type: new Abstract: Financial document validation in production, such as payroll auditing, tax compliance, and loan underwriting, demands exceptional accuracy, consistency,

Layers Matter: Why Continual Learning Regularization Should Be Layer-Adaptive

arXiv:2608.15901v1 Announce Type: cross Abstract: Continual learning regularizers like EWC fight forgetting by penalizing changes from previous-task parameters with per-parameter importance, typically

Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization

arXiv:2608.16072v1 Announce Type: cross Abstract: Reinforcement learning (RL) with group-relative advantages has become the de facto standard for post-training language model reasoners. However, when

Learning Varying Physical Therapist-Patient Interactions for Robot-mediated Upper Limb Task-Specific Training

arXiv:2608.15995v1 Announce Type: cross Abstract: Upper extremity motor function recovery is positively linked to Task-Specific Training (TST) and sufficient therapy dosage. Rehabilitation robots can

Lesioned Multimodal Language Models Reproduce Aphasic Picture-Naming Patterns

arXiv:2607.11621v2 Announce Type: replace Abstract: Aphasia following stroke commonly produces systematic naming errors with characteristic profiles, but whether general-purpose language models not de

LiD-GLM: Lipschitz-constrained Deep Generalized Linear Models

arXiv:2608.16340v1 Announce Type: cross Abstract: The combination of traditional statistical models and neural network (NN) components into semi-structured hybrid models is an intriguing approach to c

Limits to scalable evaluation at the frontier: LLM as Judge won't beat twice the data

arXiv:2410.13341v4 Announce Type: replace Abstract: High quality annotations are increasingly a bottleneck in the explosively growing machine learning ecosystem. Scalable evaluation methods that avoid

Listen, Reason, and Segment: Aligning LALMs with Editorial Judgment for Media Chapterization

arXiv:2608.16539v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) have made rapid progress on standardized benchmarks, yet their deployment in practical media workflows, curation,

LlamaRec-LKG-RAG: A Single-Pass, Learnable Knowledge Graph-RAG Framework for LLM-Based Ranking

arXiv:2506.07449v2 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have driven their adoption in recommender systems through Retrieval-Augmented Generation (RAG)

LLMs as a Jury: Cross-Model Consensus Can Outperform Process Reward Models for LLM Reasoning

arXiv:2607.10139v3 Announce Type: replace-cross Abstract: Selecting the correct answer from a pool of candidate reasoning chains is the engine of test-time scaling, yet the standard selectors each car

LLMs Can Predict Failure Risk, But Struggle to Predict Which Collaboration Protocol Pays Off: Cost-Aware Protocol Routing Across Reasoning Tasks

arXiv:2608.14927v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems can improve reasoning by spending more computation, but deployment requires deciding when extra collabora

LLMs for Zero-Shot Threat Detection via Structured Risk Indicators

arXiv:2608.16508v1 Announce Type: cross Abstract: We propose a two-stage large language model (LLM) framework for zero-shot detection of insider threats and advanced persistent threats (APTs) from het

LongDocBench: Benchmarking TOC Hierarchy and Contextual Relationship Recovery in Long Documents

arXiv:2608.15064v1 Announce Type: new Abstract: Parsing visual documents into machine-readable representations is fundamental to document intelligence. Existing benchmarks focus on page-level element

LongRCA Bench: Diagnosing Responsible Roles and Root Causes in Long-Horizon Agent Failures

arXiv:2608.15242v1 Announce Type: new Abstract: When a long-horizon agent execution fails, outcome-level evaluation reveals the unsuccessful result but not where the decisive error entered the traject