Search: “model-releases”

Linguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to Recruitment

arXiv:2609.18106v1 Announce Type: cross Abstract: Open-weight large language models are rapidly entering hiring pipelines, yet their discriminatory failure modes -- and the regulatory exposure these c

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

LM Fight Arena: Benchmarking Large Multimodal Models via Game Competition

DGX agent

arXiv:2510.08928v2 Announce Type: replace Abstract: Existing benchmarks for large multimodal models (LMMs) often fail to capture their performance in real-time, adversarial environments. We introduce

model-releasesarxiv-cs-ai

17 Sept 2026

Locating Hidden Failures Makes Long-Horizon Agents More Reliable

arXiv:2609.17930v1 Announce Type: new Abstract: As AI agents take on long, autonomous tasks, we increasingly oversee rather than perform the work, yet we still judge them almost entirely by whether th

Loco-Loco-RL: Low-Cost Terrain Mapping for Humanoid Locomotion with Reinforcement Learning

arXiv:2609.19041v1 Announce Type: new Abstract: Informative terrain perception is important for robust reinforcement learning policies in humanoid locomotion. Still, common sensors such as depth camer

Long-Lived Characters, Local Inference: Incremental Memory Maintenance for Game NPCs

arXiv:2609.18935v1 Announce Type: new Abstract: A game character should not have to reread its entire life before every conversation. For locally deployed language-model characters, however, revising

Lumen: Parameter-Efficient Alignment of Pretrained Vision and Language Encoders for Zero-Shot Computational Pathology

arXiv:2609.17868v1 Announce Type: new Abstract: Pathology vision-language models are commonly built by pretraining or fine-tuning large encoders on paired image-caption data. We asked whether a pathol

Map2Route: Benchmarking Compositional Language-Grounded Route Planning over Semantic Maps

arXiv:2609.17910v1 Announce Type: new Abstract: We introduce Map2Route, a human-curated benchmark for compositional language-grounded route planning over pre-built semantic maps. Map2Route contains 1,

Mask IPL: Noise-Free Intrinsic Position Learning via Computation Graph Clipping for Event-Based Spike-Driven Tracking

arXiv:2609.18716v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) match the event-driven nature of event cameras and naturally extract spatiotemporal features. These properties have motiv

MiST: Mid-Training LLMs for Cybersecurity

arXiv:2609.18496v1 Announce Type: cross Abstract: Cybersecurity combines high-stakes analysis with complex technical language, making it an impactful and challenging domain for LLMs. We present MiST (

Modelling Adjectival Modification Effects on Semantic Plausibility

arXiv:2507.21828v2 Announce Type: replace Abstract: While the task of assessing the plausibility of events such as 'news is relevant' has been addressed by a growing body of work, less attention has b

Modular Deep Learning Mechanisms for Auditable Next-Day Wildfire Spread Prediction

arXiv:2609.17763v1 Announce Type: new Abstract: Next-day wildfire prediction requires models whose forecasts can be evaluated alongside the assumptions and historical evidence used in their computatio

Monitoring and Discovering Reward Hacking with Internal Representations during LLM Evaluations

arXiv:2609.19101v1 Announce Type: new Abstract: As models scale, reward hacking becomes more frequent, more sophisticated, and more consequential. Does it leave a telltale signature in model represent

MoRE: Mixture of Reused Experts

arXiv:2609.18176v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures decouple model capacity from computational cost, yet incur high memory footprints as parameters grow linearly w

MSR: Multiple Subject Reference for Video Generation

arXiv:2609.18393v1 Announce Type: new Abstract: Conditioning a video generator on multiple images requires preserving appearance while associating each reference with its intended role. We present MSR

MudawanSn: A Gold-Standard Wolof-Arabic Parallel Corpus for Machine Translation

arXiv:2609.17539v1 Announce Type: new Abstract: We present MudawanSn, a gold-standard resource of 1,271 sentence-aligned pairs manually translated from Wolof into Modern Standard Arabic (MSA). The sou

Multi-Appliance Non-Intrusive Load Monitoring via Label-Preserving Aggregate Recomposition and Prediction Consistency

arXiv:2609.18315v1 Announce Type: new Abstract: Non-intrusive load monitoring (NILM) estimates appliance power sequences from aggregate power, but models trained on source households commonly lose acc

Multi-View Mixture-of-Experts with Vision-Language Reranking for Cross-View Object Geo-Localization

arXiv:2609.18139v1 Announce Type: new Abstract: Cross-view object geo-localization (CVOGL) locates a target in satellite imagery using drone or street-view queries. Existing methods train separate det

Multimodal Behavior Tree Generation: A Small Vision-Language Model for Robot Task Planning

arXiv:2603.06084v2 Announce Type: replace Abstract: Large language models have been widely used for robotic task planning, often taking advantage of representations such as Behavior Trees (BTs). Visio

Multimodal Conditioning of Fine-Tuned Stable Diffusion XL for Controllable and Culturally Faithful Ulos Motif Generation

arXiv:2609.17987v1 Announce Type: new Abstract: The traditional Batak Ulos weaving industry faces growing challenges in producing diverse, innovative motifs due to limitations in conventional, manuall

MUSE: Benchmarking Large Vision-Language Models on Multi-Modal Understanding in Situated Education

arXiv:2609.19088v1 Announce Type: new Abstract: Large vision-language models have achieved remarkable progress in multi-modal understanding, yet their capabilities in educational settings remain insuf

NanoBench: A Multi-Task Benchmark Dataset for Nano-Quadrotor System Identification, Control, and State Estimation

arXiv:2603.09908v2 Announce Type: replace Abstract: Existing aerial-robotics benchmarks target vehicles from hundreds of grams to several kilograms and typically expose only high-level state data. The

NeMo Data Designer: An Extensible Framework for Multimodal Synthetic Data Generation

arXiv:2609.17699v1 Announce Type: new Abstract: We present NeMo Data Designer (NDD), an open-source, general-purpose framework for multi-modal synthetic data generation (SDG). Designed to be intuitive

No Usable Linear 'Capitulation Direction' in Two Small LLMs: A Validation Protocol for Activation-Steering Claims, and a Cross-Family Behavioral Study of Sycophancy Under Pushback

arXiv:2609.17550v1 Announce Type: new Abstract: Language models frequently abandon correct answers when users push back. We study this in two small instruction-tuned models from different families, Qw

NObSP: Functional Decomposition of Neural Networks via Oblique Subspace Projections

arXiv:2609.17825v1 Announce Type: new Abstract: Understanding how deep neural networks make decisions remains a fundamental challenge. We present NObSP (Nonlinear Oblique Subspace Projections), a fram

Not All Layers Need Tuning: Diagnosing and Directing Adaptation in Vision-Language-Action Models

arXiv:2609.18084v1 Announce Type: cross Abstract: Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to ev

OBC-Prune: Outcome-Based Calibration for Large Reasoning Model Pruning

arXiv:2609.17890v1 Announce Type: new Abstract: Large reasoning models (LRMs) generate long chain-of-thought traces before answering, creating significant inference overhead. Pruning can reduce this c

Occluded Gait Recognition with Mixture of Experts: An Action Detection Perspective

arXiv:2609.18432v1 Announce Type: new Abstract: Extensive occlusions in real-world scenarios pose challenges to gait recognition due to missing and noisy information, as well as body misalignment in p

On the Identifiability of Mixed Ordinal and Exponential Family Causal DAGs under Linear Parametric Models

arXiv:2609.17942v1 Announce Type: new Abstract: The problem of identifiability in linear parametric models (LPMs) whose nodes follow either an ordered logit model or a regular one-parameter exponentia

One Color Preprocessing Improves DSATUR

arXiv:2609.17633v1 Announce Type: new Abstract: The Graph Coloring Problem (GCP) is NP-hard and DSATUR stands as one of the fastest heuristics for it despite producing colorings that typically use mor

PACT: Can Enterprise AI Assistants Be Trusted Under Pressure?

arXiv:2609.18605v1 Announce Type: cross Abstract: As corporate AI adoption continues to grow, enterprise-grade LLM agents are being deployed into sensitive contexts such as hiring, healthcare, and fin

PANORAMA: Panoptic Grounded Captioning via Mask Proposal Selection

arXiv:2609.19143v1 Announce Type: cross Abstract: Intelligent systems that act in the world require image understanding that is both comprehensive and spatially grounded. Current vision-language model

PBEBench: A Multi-Step Programming by Examples Reasoning Benchmark inspired by Historical Linguistics

arXiv:2505.23126v5 Announce Type: replace Abstract: Although many benchmarks evaluate the reasoning abilities of Large Language Models (LLMs) within domains such as mathematics, coding, or data wrangl

PDA++: Field-Aligned Planning and Scene-Adaptive Insertion in Remote Sensing

arXiv:2609.18329v2 Announce Type: new Abstract: Remote sensing recognition is often constrained by scarce observations of rare targets and costly annotations, making realistic synthetic augmentation p

PentestChain: A Cost-Aware, MCP-Orchestrated Framework for Automated Penetration Testing with Free-Tier LLMs

arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, au

PersonaPath: Towards Knowledge-Centric Personalized Learning Path Planning

arXiv:2609.18861v1 Announce Type: new Abstract: Adaptive learning systems commonly formulate learning path planning as Exercise-Centric (EC) recommendation, where the next step is inferred from item-l

Physics-Informed Neural Networks for Fast Multilayer Spectral Inversion of H{alpha} 6562.8 A and Ca II 8542.1 A Spectra

arXiv:2609.18025v1 Announce Type: cross Abstract: Strong chromospheric absorption lines such as Halpha 6562.8 A and Ca II 8542.1 A provide vital diagnostics of plasma dynamics and thermal structure in

Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance Spectroscopy

arXiv:2505.03590v2 Announce Type: replace-cross Abstract: Magnetic resonance spectroscopy (MRS) is a non-invasive technique to measure the metabolic composition of tissues, offering valuable insights

Planning or Improvisation? Stress-Testing the Poetry Planning Site on Open Models and Open Cross-Layer Transcoders

arXiv:2609.18440v1 Announce Type: new Abstract: Lindsey et al. (2025) report that Claude 3.5 Haiku plans rhymes: features for candidate rhyme words are active on the newline before a line is written,

Playing log(N)-Questions over Wikipedia Abstracts: Communication Efficiency Between Paired Frontier Models

arXiv:2609.19113v1 Announce Type: new Abstract: We evaluate six frontier language models on the two-agent log(N)-Questions game. A questioner sees N Wikipedia lead paragraphs and must identify a secre

PointZero: 3D Point Track Completion for Learning Transferable 3D Dynamics

arXiv:2609.19142v1 Announce Type: cross Abstract: World models endow perceptual systems with the ability to predict how scenes evolve under interaction. They are most beneficial when trained on divers

Position Anchor Tuning: Towards Efficient Adaptation of Pre-Trained Point Cloud Transformers

arXiv:2609.18056v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) has recently emerged as a pivotal research direction for adapting pre-trained point cloud transformers to diverse

Procedural Pretraining for Molecular Property Prediction

arXiv:2609.17831v1 Announce Type: cross Abstract: Molecular property prediction is often limited by the small size of labeled downstream datasets, motivating pretraining on large corpora of unlabeled

ProgramDistill: From Interactive Web Apps to Verifiable Reference-Guided SWE Tasks

arXiv:2609.18805v1 Announce Type: cross Abstract: Coding agents are typically evaluated with desired behavior specified through issues or instructions. In practical web development, however, agents ma

Prosthesis-Aware 3D Human Pose Estimation: A Dataset and Benchmark for RSP Users

arXiv:2609.18406v1 Announce Type: new Abstract: Recovering 3D human body motion from video is important for applications such as rehabilitation assessment and sports performance evaluation. For prosth

QEMScore: How Much Does the Measurement Add to Learned Quantum Error Mitigation?

arXiv:2609.17896v1 Announce Type: cross Abstract: How much does the noisy measurement add to learned quantum error mitigation? An accuracy table cannot say, because a model handed circuit structure ca

RAF-VLA: Representation Alignment with the Future for End-to-End Autonomous Driving

arXiv:2609.17728v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models for autonomous driving have incorporated world modeling by predicting future driving scenes alongside driving

Reading Between the Lines: Can LLMs Discover the Question Behind the Text?

arXiv:2609.19070v1 Announce Type: new Abstract: This paper introduces ``question archaeology'', a specific evaluation task focused on inferring the single, authentic 'genesis question' that motivated

Recursive Reasoning or Statistical Extrapolation? In-Context Learning in Multi-Agent Interdependent Decision-Making

arXiv:2609.18591v1 Announce Type: new Abstract: In-context learning (ICL) enables large language model (LLM) agents to improve decisions using interaction history, yet it remains unclear whether such