Search: “model-releases”

NAST: Improving Negation Handling in Medical Vision-Language Models through Negation-Aware Selective Training

arXiv:2602.12498v2 Announce Type: replace Abstract: Negation is a fundamental linguistic operation in clinical reporting, yet vision-language models (VLMs) frequently fail to distinguish affirmative f

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Neural Network-Based Parameter Estimation of a Labour Market Agent-Based Model

DGX agent

arXiv:2602.15572v3 Announce Type: replace Abstract: Agent-based modelling (ABM) is a widespread approach to simulate complex systems. Advancements in computational processing and storage have facilita

model-releasesarxiv-cs-lg

17 Aug 2026

Non-Parametric Spatiotemporal Trajectory Prediction via State-Conditioned Transition Sampling

arXiv:2608.14349v1 Announce Type: new Abstract: We present a training-free method for multi-modal trajectory prediction that achieves comparable accuracy to a 57M-parameter transformer while requiring

On the Robustness of Temporal Vision-Language Models for Surgical Endoscopy Videos

arXiv:2608.14262v1 Announce Type: new Abstract: Temporal vision-language models (TVLMs) offer a reusable, prompt-based interface for surgical video understanding, yet, their robustness under clinicall

OpenBelief-Nav: Evidence-Preserving Object Memory for Open-Vocabulary Language-Guided Navigation

arXiv:2608.13923v1 Announce Type: new Abstract: Open-vocabulary 3D scene graphs provide compact semantic memory for language-guided navigation, but mapped objects are often exposed through a single fu

Ordinal-Aware Calibration for Ordinal Classification

arXiv:2410.15658v4 Announce Type: replace-cross Abstract: Deep neural networks frequently produce overconfident, miscalibrated predictions. In ordinal classification, predictions must also adhere to a

Owner3D: Ownership-Guided Style Writing for Training-Free Localized 3D Stylization

arXiv:2608.14078v1 Announce Type: new Abstract: Localized 3D stylization aims to modify the appearance of a specified object part while preserving the remaining surfaces. In large reconstruction model

P2Skill: Privacy Preserving Skill Distillation for Cloud-Local LLM Inference Systems

arXiv:2608.14094v1 Announce Type: cross Abstract: Cloud-local LLM inference systems have the potential to use the reasoning capability of large cloud models while protecting sensitive user data on per

PACE-Bench: Benchmarking Physics Adaptation via Code Evolution in Dynamic Environments

arXiv:2608.14441v1 Announce Type: new Abstract: Self-evolving agents improve future behavior from interaction experience, yet existing evaluations typically optimize under fixed execution conditions a

PEFT-MuTS: A Multivariate Parameter-Efficient Fine-Tuning Framework for Remaining Useful Life Prediction based on Cross-domain Time Series Representation Model

arXiv:2601.22631v2 Announce Type: replace-cross Abstract: The application of data-driven remaining useful life (RUL) prediction has long been constrained by the availability of large amount of degrada

PRM-as-a-Judge 1.5: A Toolkit for Robot Process Assessment

arXiv:2608.14284v1 Announce Type: cross Abstract: Fine-grained robotic evaluation matters for understanding embodied models, going beyond binary success rates and rule-based process scores. We present

QUASAR: Lowering the Loss Floor of Quantization-Aware Training with Loss-Aware Reconstruction

model-releasesarxiv-cs-cl

arXiv:2608.13966v1 Announce Type: cross Abstract: As large language model inference shifts toward lower precision, post-training quantization (PTQ) becomes increasingly brittle, making quantization-aw

QuaSAR: Quantization Compensation via Stable Activation-Aware Rank Truncation

arXiv:2608.14149v1 Announce Type: new Abstract: Recent training-free post-training quantization methods restore model accuracy through closed-form residual compensation. To constrain additional model

Recent Advances in Deep Learning-Based Drug-Target Binding Affinity Prediction

arXiv:2608.13797v1 Announce Type: new Abstract: Computational approaches to drug discovery involve multiple sub-problems, and among them, drug-target binding affinity prediction plays an important rol

Redefining Generalization in Visual Domains: A Two-Axis Framework for Fake Image Detection with FusionDetect

arXiv:2510.05740v2 Announce Type: replace-cross Abstract: The rapid development of generative models has made it increasingly crucial to develop detectors that can reliably detect synthetic images. Al

Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation

arXiv:2608.14379v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently achieved promising performance in robotic manipulation. However, existing benchmarks mainly evaluate

Regime-Conditional Verification: Correctness Estimation for Adapting and Monitoring Safety Classifiers

arXiv:2608.14089v1 Announce Type: new Abstract: Safety classifiers deployed with large language models often fail for two reasons: their decisions reflect the policy learned during training rather tha

Reinforcement Learning-Based Production Scheduling in an Industry-Based Coating Scenario Using the Digital Model Playground

arXiv:2608.14122v1 Announce Type: new Abstract: Production scheduling in complex manufacturing environments is challenging when sequence-dependent setup times, stochastic disturbances, and due-date co

Resource-Efficient RGB-Only Action Recognition for Edge Deployment

arXiv:2602.10818v2 Announce Type: replace Abstract: Resource-constrained assistive monitoring requires compact local video perception and an explicit understanding of how recognition reliability chang

Rethinking Automated Program Repair: The Impact of Bug Complexity, Fault Localization, and LLM Cost-efficiency

arXiv:2608.14065v1 Announce Type: cross Abstract: Background: Software bugs remain a critical challenge in development, necessitating effective Automated Program Repair (APR) techniques. While Large L

Retrieve-then-Adapt: Retrieval-Augmented Test-Time Adaptation for Sequential Recommendation

arXiv:2604.05379v2 Announce Type: replace-cross Abstract: The sequential recommendation (SR) task aims to predict the next item based on users' historical interaction sequences. Typically trained on h

Revisiting Shape and Texture Reliance with Category-Separability-Calibrated Suppression

arXiv:2607.16298v2 Announce Type: replace Abstract: Feature-suppression evaluations infer model reliance on shape or texture from the accuracy loss caused by attenuating each type of information. Such

Rewrite Once, Validate Anywhere: Producing OWL-Aware SHACL Constraints (Extended Version)

arXiv:2608.14104v1 Announce Type: cross Abstract: The Shapes Constraint Language (SHACL) is a W3C recommendation to express syntactic constraints, called shapes, on RDF graphs. SHACL validators are us

RL-Index: Reinforcement Learning for Retrieval Index Reasoning

arXiv:2606.16316v2 Announce Type: replace-cross Abstract: Retrieving external knowledge is crucial for real-world tasks but remains difficult when queries and relevant knowledge are linked by implicit

Robust Dual-Model Collaborative Random Vector Functional Link Network

arXiv:2608.13628v1 Announce Type: new Abstract: Random vector functional link (RVFL) networks are lightweight and fast neural models that offer efficient training and strong generalization through ran

Rollplex: Cross-Phase GPU Spatial Sharing for Vision Language Model Post-Training

arXiv:2608.14498v1 Announce Type: new Abstract: Vision-language models (VLMs) enable embodied agents to reason and act from visual observations and language instructions. Reinforcement learning (RL) p

SAGE: Surrogate-gradient Adaptation via Attention-Guided Entropy for Spiking Transformers

arXiv:2608.13702v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) offer an energy-efficient alternative to conventional deep neural networks by exploiting sparse event-driven computatio

Scaling Domain Data Repetition in LLM Pretraining

arXiv:2608.14071v1 Announce Type: new Abstract: As large language models scale, their training-token budgets must also increase to maintain an appropriate tokens-per-parameter ratio ((TPP)). However,

SDO: Subspace Deconflicting Operator for Multi-Adapter Composition

arXiv:2608.13820v1 Announce Type: new Abstract: Composing independently trained adapters within a shared diffusion backbone provides a modular approach to multi-character generation, but naive joint d

Second Thought: Reasoning in Parallel as LLM Agents Act and Observe

arXiv:2608.13667v1 Announce Type: new Abstract: LLM agents in the ReAct paradigm alternate between reasoning, acting, and observing, but deliberate reasoning is confined to the Thought phase: while th

Self-Supervised Visual On-Policy Distillation

arXiv:2608.14144v1 Announce Type: cross Abstract: Visual on-policy distillation relies heavily on an informative teacher-student asymmetry, through either a larger, stronger teacher or privileged supe

SemPlan: Benchmarking Structured Semantic Planning for LLM-Based Queries over Enterprise Data

arXiv:2608.13612v1 Announce Type: new Abstract: Natural-language interfaces to enterprise data must translate underspecified requests into governed, executable behavior while controlling invalid queri

SimpleOPD: Simple Tokenizer-Agnostic On-Policy Distillation for Long-Context Reasoning

arXiv:2608.14277v1 Announce Type: cross Abstract: On-policy distillation (OPD) offers a promising way to transfer reasoning capabilities from stronger teacher models, but applying it to long-context r

Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinement

arXiv:2608.13767v1 Announce Type: new Abstract: Analog IC layout design remains a labor-intensive iterative process dominated by simulation-driven refinement. Although end-to-end layout generators acc

TENET: One Step Toward Test-Driven Development for Repository-Level Code Generation

arXiv:2509.24148v4 Announce Type: replace-cross Abstract: Test-Driven Development (TDD) is a widely adopted practice that requires developers to create and execute tests alongside implementation. With

The Architect: Interactive Visualization of Deep Learning Mathematics Directly in Microsoft Excel

arXiv:2608.13572v1 Announce Type: cross Abstract: We present The Architect, a system that turns Microsoft Excel into an interactive view of deep learning mathematics. A user describes a neural network

The Dynamics of Intelligence Explosions

arXiv:2608.14426v1 Announce Type: new Abstract: AI is increasingly being used to help with AI R&D. Under certain conditions this feedback loop might be able to produce an intelligence explosion, with

The Integer Alibi: Localizing Cross-Kernel Divergence in INT8-Quantized LLM Inference

arXiv:2608.13756v1 Announce Type: new Abstract: Two GPU kernels implementing the same scaled INT8 GEMM interface are usually treated as interchangeable. We test that assumption: holding the checkpoint

The Metacognitive Bottleneck: Japanese Riddles Reveal Fundamental Limits of Machine Insight and Self-Evaluation in Reasoning AI

arXiv:2509.14704v3 Announce Type: replace Abstract: Benchmark saturation and training-data contamination increasingly obscure whether reported gains in large language models (LLMs) reflect genuine adv

TimeSage-EV: A Live Benchmark for Agentic Time Series Analysis in Evolving Environments

arXiv:2608.14270v1 Announce Type: new Abstract: Time series analysis in high-stakes domains relies on recurring data releases, where new observations can alter the evidence base and the validity of la

Twin: Playing an Unknown Game with a Test-Time Digital Twin

arXiv:2608.14490v1 Announce Type: new Abstract: We present a Test-time World-model Inference (Twin) system, in which a frontier coding agent writes an executable world model for completing continual l

Voxel-based 3D Facies Segmentation from Seismic Data: A Comparative Study

arXiv:2608.14058v1 Announce Type: cross Abstract: Seismic facies segmentation has emerged as a significant challenge in geophysics, requiring robust methods and systems to effectively identify geologi

When Personal Memory Has No Single Answer: Evaluating LLM Agents under Irreducible Conflict

arXiv:2608.13921v1 Announce Type: new Abstract: LLM agents increasingly maintain personal memory across sessions, but it can conflict. Preferences depend on context, behavior evolves, and sources can

Whose doctor does the AI recommend? An algorithm audit of reputation and demographic signals in large language model-assisted physician choice

arXiv:2608.14399v1 Announce Type: cross Abstract: Patients increasingly ask large language model (LLM) assistants which doctor to see, making these systems AI infomediaries: algorithms that intermedia

Wrong but Useful: Trajectory Value Beyond Answer Correctness in Multi-Agent Messages

arXiv:2608.14375v1 Announce Type: new Abstract: Multi-agent reasoning systems often use agreement, confidence, or automated scores to decide which messages should shape a final answer. Such filtering

XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas

arXiv:2602.04819v5 Announce Type: replace Abstract: Accurate risk stratification of precancerous polyps during routine colonoscopy screening is a key strategy to reduce the incidence of colorectal can

You Only Pass Once: Answering and Abstaining Together in a Single Forward Pass of a Frozen Language Model

model-releasesarxiv-cs-cl

arXiv:2608.14465v1 Announce Type: new Abstract: A frozen language model on reasoning tasks has two coupled weaknesses: it under-uses evidence its own residual stream already encodes, and it fails to d

Zero-Shot Skeleton-Based Action Anticipation

arXiv:2608.14243v1 Announce Type: new Abstract: Action anticipation (AA) aims to recognize ongoing human or humanoids actions from partial observations, enabling robots to predict intentions before th