model releases

Knowing When to Stop: Efficient Context Processing via Latent Sufficiency Signals

arXiv:2502.01025v4 Announce Type: replace Abstract: Large language models (LLMs) process entire input contexts indiscriminately, which is inefficient when the information required to answer a query is

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Model Releases

Language Models Have Interpretable Narrative Mechanisms

DGX agent

arXiv:2610.12989v1 Announce Type: new Abstract: We investigate whether language models contain internal components that contribute to representing narrativity, the degree to which a text exhibits narr

model-releasesarxiv-cs-cl

12 Oct 2026

Les Miserables Dialogue: A film-based network representation of social communication

arXiv:2610.13148v1 Announce Type: cross Abstract: In this work, we revisit the classic Les Miserables benchmark network from the perspective of social communication. Using the 1998 film adaptation of

Let Large Language Models Judge Each Other: Multi-Agent Peer-Reviewed Reasoning for Medical Question Answering

arXiv:2606.15419v2 Announce Type: replace-cross Abstract: Objective: To enhance the accuracy, interpretability, and robustness of large language models (LLMs) in medical question answering (MedQA). Me

Lightweight Time-Frequency Vibration Sensing for Consumer Device Condition Monitoring

arXiv:2610.13040v1 Announce Type: cross Abstract: Consumer rotating devices, including washing machines, air conditioners, electric fans, robotic vacuum cleaners, and home fitness equipment, increasin

LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection Challenge

arXiv:2506.09956v2 Announce Type: replace-cross Abstract: Indirect prompt injection attacks exploit a fundamental weakness of LLMs: executing unauthorized tasks from untrusted sources. Despite the pra

Local Diagnostics of Learned Event Representations for Anomaly Detection at the HL-LHC

arXiv:2610.13437v1 Announce Type: new Abstract: Anomaly detection, the identification of collision events that deviate from Standard Model expectations, is one of the most promising model-agnostic str

Localized Generative Design of Ship Hulls with Diffusion Models and High-Fidelity Assessment

arXiv:2610.12870v1 Announce Type: cross Abstract: Practical ship design requires localized refinement and performance evaluation. This paper presents a reward-directed diffusion framework for localize

Locate, Judge, Read: Role-Specialized Tool Agents over a Knowledge-Point Index for Open-Domain Multimodal Document QA

arXiv:2610.13128v1 Announce Type: new Abstract: Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-

LongHarness: Advancing Agentic Reasoning over 100M-Token Corpora via Stateful Evidence Management

arXiv:2610.13075v1 Announce Type: new Abstract: Corpus-level long-context reasoning requires agents to acquire and integrate evidence across document collections that exceed their context windows. Exi

Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics

arXiv:2610.12518v1 Announce Type: cross Abstract: This position paper argues that the generative molecular dynamics (GenMD) community is not properly evaluating its progress: current evaluations let a

LSearch - Spotlight for windows with embedding

model-releasesr-localllama

I built a spotlight search for windows. It has an embedding model and a MoE models to go with it. The MoE It's 2 Qwen 3.5 4B models, I fine tuned one for coding work and another for agentic work, and

Machine Learning and Time-Series Foundation Models for Day-Ahead Electricity Forecasting in a University Building

arXiv:2610.12638v1 Announce Type: cross Abstract: Day-ahead electricity forecasts can help building operators schedule heating, ventilation, and other services around anticipated demand. Choosing a fo

MADS: Multi-Agent Dialog Simulation for Robust Conversational Agents

arXiv:2610.12757v1 Announce Type: new Abstract: Task-oriented conversational agents remain fragile under realistic conditions, especially when users exhibit non-cooperative behavior. Existing function

MagicBeanStalk: Escaping the RLVR Zero Advantage Trap with Recursive Data Synthesis

arXiv:2610.12659v1 Announce Type: new Abstract: Data-centric scaling of RLVR has focused on collecting or generating verifiable training problems. However, corpus size alone does not determine whether

MAGMA-Bench: Evaluating Long-Horizon Embodied Agents under Dynamic Tasks and Execution Failures

arXiv:2610.13534v1 Announce Type: new Abstract: Long-horizon embodied agents must maintain task-relevant information, coordinate heterogeneous robots, and adapt their decisions as execution unfolds. E

ManeuverFlow: Maneuver Hypothesis Generation with Future Evidence for Trajectory Evaluation and Refinement in End-to-End Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2610.13409v1 Announce Type: new Abstract: End-to-end planning in complex scenes must model diverse driving intentions and select the most appropriate trajectory using scene context and future ri

Market Impact Estimation via Causal Foundation Models

arXiv:2610.12537v1 Announce Type: new Abstract: When a trader executes a large order, the relevant question is not what will the price be? but what would the price have been had I not traded? Market i

Masked Diffusion Language Agents for Tool-Integrated Chemical Reasoning

arXiv:2610.13330v1 Announce Type: new Abstract: Designing tool-integrated reasoning agent systems for complex chemical tasks remains a fundamental challenge. Although recent chemical agents have demon

MathVis: Can AI Reason through Drawing? A Benchmark for Mathematical Figure Generation

arXiv:2610.12954v1 Announce Type: new Abstract: This paper introduces MathVis, a benchmark designed to evaluate LLMs' ability to visualize frontier mathematical problems and perform diagram-assisted r

MC-EvoBench: Auditing Experience-Driven Self-Improvement in Minecraft Agents

arXiv:2610.13829v1 Announce Type: cross Abstract: A central challenge in embodied recursive self-improvement is enabling agents to convert interaction history into capabilities that persist beyond one

MENTOR: Learning from Failure with On-Policy Pedagogical Intervention

arXiv:2610.13594v1 Announce Type: new Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) is a key driver for Large Reasoning Models, but it is vulnerable to 'zero-reward collapse', a trai

MetaJoin: Adaptive Join Selections for Heterogeneous Tables

arXiv:2512.02444v2 Announce Type: replace-cross Abstract: Joining heterogeneous tables requires different forms of correspondence, including exact agreement, syntactic transformation, semantic similar

Mind the Spatial Gap: A Benchmark for Geospatial Reasoning and Constrained Spatial Editing

arXiv:2610.12881v1 Announce Type: new Abstract: Understanding and manipulating spatial relations is fundamental to AI systems that reason about physical environments and construct grounded world model

Mixture of Many Zero-Compute Experts: A High-Rate Quantization Theory Perspective

arXiv:2510.03151v2 Announce Type: replace Abstract: This paper uses classical high-rate quantization theory to provide new insights into mixture-of-experts (MoE) models for regression tasks. Our MoE i

MolP2SBench: Do LLMs Really Reason from Molecular Properties to Structure?

arXiv:2610.12522v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in molecular discovery and structure elucidation, where decisions depend on physical observations.

MoPrO-SD: Modular Prompt Optimization for Stance Detection

arXiv:2610.13386v1 Announce Type: new Abstract: Stance detection remains challenging for large language models (LLMs) due to implicit opinions, sarcasm, and context-dependent expressions of stance. Al

MS-GLA: Multi-Scale Gated Linear Attention for Addressing Representational Bottlenecks via Multi-Temporal Resolution

arXiv:2609.35664v2 Announce Type: replace-cross Abstract: Gated Linear Attention (GLA) Transformers advance linear recurrent models through data-dependent gating, but face a core limitation: the fixed

MVGraph: Benchmarking LVLMs on Evidence Composition across Multi-View Visual Graph

arXiv:2610.12961v1 Announce Type: cross Abstract: We introduce MVGraph, a benchmark for evaluating large vision-language models (LVLMs) on multi-graph reasoning where the evidence required by a query

Neurograf v1: An End-to-End Romanian-First Language Model Family

arXiv:2610.13134v1 Announce Type: new Abstract: We present Neurograf v1, an experimental end-to-end Romanian-first language-model pipeline developed to investigate the feasibility of training language

NeuronSpark: Selective Spiking State Space Models with Adaptive Computation for Language Modeling

arXiv:2603.16148v2 Announce Type: replace Abstract: Spiking neural networks promise brain-inspired neural dynamics, yet native large-scale spiking language-model pretraining remains largely unexplored

Not All Correct Fixes Run Alike: An Empirical Study of Patch Performance in Repository-Level Issue Resolution

arXiv:2610.13563v1 Announce Type: cross Abstract: Repository-level issue-resolution benchmarks such as SWE-bench evaluate submitted patches primarily based on whether they pass the correctness tests,

NovaSplat: Model-Free 6D Object Pose Estimation via 3D Gaussian Splatting Onboarding and Refinement

model-releasesarxiv-cs-ro

arXiv:2610.13309v1 Announce Type: cross Abstract: 6D pose estimation of novel objects without CAD models remains an open challenge: model-free methods must build the object representation from scratch

NV-Tesseract-AD: Curriculum-Enhanced Conditional Diffusion for Multivariate Time-Series Anomaly Detection

arXiv:2610.12754v1 Announce Type: new Abstract: We propose NV-Tesseract-AD, a curriculum learning-enhanced conditional diffusion framework for multivariate time-series anomaly detection. Our central h

OccludeBench: Can VLMs Find What's Missing?

arXiv:2610.13790v1 Announce Type: cross Abstract: How well can vision-language models (VLMs) reason about what is missing from an image? We study this question with OccludeBench, a manually curated be

OGPO: Offline Goal-conditioned Policy Optimization for Recoverable Vision-Language-Action Models

arXiv:2610.12914v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong promise in robotic manipulation, yet their post-training still predominantly relies on trajectory-

Oido: Open-Vocabulary Speech Recognition on a $5 Microcontroller without a Neural Accelerator

arXiv:2610.13447v1 Announce Type: cross Abstract: Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands. We present Oido, an inferenc

Optimizable Model Averaging for Ensembling Heterogeneous Model Outputs

arXiv:2505.21857v2 Announce Type: replace Abstract: Foundation model ensembles can improve accuracy and robustness, but full fine-tuning and parameter-space merging are often expensive or impossible w

PANDA: Prior-guided Attentional Dual-path Architecture

arXiv:2610.13635v1 Announce Type: new Abstract: Hypergraph Neural Networks (HNNs), designed to model higher-order relations beyond pairwise interactions, typically rely either on fixed structural weig

People Making Conversation: Evaluating How Naturally Speech Models Converse

arXiv:2610.12802v1 Announce Type: new Abstract: A conversational speech model has to decide, at every pause, whether to speak. Existing evaluations test boundary detection, policy adherence, or aggreg

Personalization Without Stereotyping: Do Speech LLMs Know When to Turn a Deaf Ear?

arXiv:2610.13550v1 Announce Type: new Abstract: Recent speech LLMs can leverage rich paralinguistic cues, enabling more complex and personalized interactions. However, little work investigates how thi

perturber: A Stateless Service for Semantics-Preserving Text Perturbations

arXiv:2610.12667v1 Announce Type: new Abstract: Large language model (LLM) evaluations on clean benchmarks overstate model robustness: real inputs arrive perturbed, and these meaning-preserving varian

PlacePulse: Learning Transferable Place Representations from Structural Geographic Data

arXiv:2610.13390v1 Announce Type: new Abstract: Geospatial machine learning often depends on task-specific feature engineering over large collections of sociodemographic, business, and environmental v

Planning with Transformers: Chain of Computation and Structured Context Windows

arXiv:2607.17710v2 Announce Type: replace Abstract: Large Language Models (LLMs) have had a remarkable impact across many areas of machine learning. However, recent studies have shown that they strugg

PPG-Bench: A Unified Benchmark for PPG Foundation Models

arXiv:2610.13435v1 Announce Type: new Abstract: Photoplethysmography (PPG) is increasingly recorded by wearable and clinical devices at enormous scale, and a growing number of PPG foundation models (F

Private and Distributionally Robust Federated Multiclass Classification

arXiv:2610.13631v1 Announce Type: new Abstract: Fault diagnosis in asset-intensive industries requires multiclass models trained on noisy, sensitive data collected across geographically distributed cl

Provenance-Aware Belief Updating in Human-AI Feedback Loops

arXiv:2610.13008v1 Announce Type: new Abstract: In repeated human-AI interaction, a single observation can be quoted, summarized, and returned to a model as multiple reports, making repetition look li

QLoRA on ExLlamaV3 Quants - Train @ 2-8bpw

model-releasesr-localllama

EXL3-QLoRA I've built this over the last few months and I think it's stable enough to share now. A fork of ExLlamaV3, this is a native ExLlamaV3 training implementation with plain PyTorch, without tra