Search: “models”

Making Clinical Language Models Auditable: Concept-Guided Fine-Tuning for Robust Prediction

arXiv:2608.27397v1 Announce Type: cross Abstract: Clinical language models can achieve strong in-hospital accuracy yet fail under deployment shifts because they exploit note-specific artifacts (e.g.,

28 Aug 2026

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Pushing the Envelope of LLM Inference with Ultra-Low-Bit Quantized Models

DGX agent

arXiv:2508.06753v3 Announce Type: replace Abstract: The advent of ultra-low-bit LLM models, approaching the perplexity and task accuracy of their full precision counterparts, is ushering in a new era

hardwarearxiv-cs-ai

28 Aug 2026

Self-OPD: On-Policy Distillation for Flow Matching Models without Teacher

arXiv:2608.26872v1 Announce Type: new Abstract: On-policy distillation (OPD), which leverages a pre-trained, specialized teacher model to provide dense supervisory signals, has achieved significant su

safetyarxiv-cs-cv

28 Aug 2026

Thomson: Continual Learning of Frontier Models for SovereignAI

arXiv:2608.27147v1 Announce Type: new Abstract: The development of frontier models is commonly perceived to be the exclusive remit of a small number of heavily funded players, creating an information,

safetyarxiv-cs-ai

28 Aug 2026

ConfAL-WM: Confidence-Guided Active Learning for Action-Conditioned World Models

arXiv:2608.25572v1 Announce Type: new Abstract: Action-conditioned world models have become an important foundation for embodied prediction, planning, and synthetic data generation, but their errors u

researcharxiv-cs-ro

Fusing Perceptual Vision Experts with Multimodal Large Language Models for Explainable Plant Disease Diagnosis: From Benchmark Imagery to Real-World Robotic Field Validation

arXiv:2608.24934v1 Announce Type: new Abstract: Accurate field plant disease diagnosis requires reliable fusion of uncertain and conflicting perceptual evidence. We present the Hybrid Hierarchical Mul

IDEAlign: Comparing Ideas of Large Language Models to Domain Expert

model-releasesarxiv-cs-cl

arXiv:2509.02855v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to produce open-ended, interpretive annotations, yet there is no validated, scalable measure of i

Output Dilution: Redundant but Fragile Representations in MoE Models

arXiv:2608.25231v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models appear to encode moral content as robustly as dense models, yet prove far more fragile in their encoding. In OLMoE-1B-

researcharxiv-cs-cl

Semi-Supervised Adaptation of Vision-Language Models for Image Classification

arXiv:2608.25485v1 Announce Type: new Abstract: Vision-language models like CLIP have shown sig- nificant potential in handling natural images, yet their perfor- mance is often limited by the distinct

Do Robotic World Models Really Follow Actions? Diagnosing and Aligning Action-Conditioned Generation for Policy Learning

arXiv:2608.24885v1 Announce Type: cross Abstract: Action-conditioned world models are increasingly used as learned simulators for policy evaluation and improvement, yet their effectiveness rests on an

safetyarxiv-cs-cv

26 Aug 2026

Preference Data Selection for Mitigating the Alignment Tax in Large Language Models

arXiv:2608.24192v1 Announce Type: new Abstract: Aligning large language models to human preferences is crucial for real-world deployment but frequently incurs an alignment tax, leading to the catastro

26 Aug 2026

Scalable and Versatile Identification for Hierarchical Structural Causal Models: A New Look at Project STAR

arXiv:2608.24500v1 Announce Type: cross Abstract: The STAR (Student-Teacher Achievement Ratio) experiment (1985, Tennessee, USA) is a landmark hierarchical dataset designed to assess the impact of cla

26 Aug 2026

A Data-Driven Approach to State Construction in Markov Models

arXiv:2608.21480v1 Announce Type: cross Abstract: A Markov chain is a widely used stochastic process modelling random events over time. These models are built on subsets of the entire dataset, referre

A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs

arXiv:2506.20073v2 Announce Type: replace-cross Abstract: Spatio-temporal data mining plays a pivotal role in informed decision making across diverse domains. However, existing models are often restri

BanglaVeilGuard: Cross-Script Safety Benchmarking and Lightweight Guardrails for Bangla Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.21880v1 Announce Type: new Abstract: Bangla large language model (LLM) safety is difficult to evaluate with English-centric or standard-script benchmarks because Bangla users routinely writ

Beyond Instance Slots: Semantically Rich World Models for Physical Interaction Planning

arXiv:2608.22294v1 Announce Type: new Abstract: World models for physical interaction are typically trained to predict future observations or latent features; however, a planning-oriented model must a

researcharxiv-cs-ro

CounterAlign: Counterfactual Supervision for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2608.21740v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are typically trained with behavior cloning (BC) on expert demonstrations. However, BC provides only positive superv

Data-Driven Dynamic Algorithm Dispatch with Large Language Models

arXiv:2608.21584v1 Announce Type: new Abstract: We introduce a large language model (LLM)-driven approach for generating dynamic algorithmic dispatch heuristics in high-performance linear algebra. By

DiagFlowBench: Evaluating How Language Models Handle Off-Procedure Inputs in Grounded Diagnostic Dialogue

arXiv:2606.17904v2 Announce Type: replace Abstract: Language models increasingly serve as advisory systems in maintenance operations. To prevent hallucination, recent systems ground these models in pr

ExplainGuard: A Zero Trust Framework for Post-Hoc Explanation Integrity Guarantees in Blackbox XAI Models

arXiv:2608.21803v1 Announce Type: cross Abstract: As machine learning (ML) models are increasingly deployed in high-stakes environments, explainable AI (XAI) methods like SHAP and LIME have become ess

GeoWAM: Visual Geometry World Action Models for Autonomous Driving

arXiv:2608.23486v1 Announce Type: new Abstract: World action models (WAMs) have recently gained increasing attention as a framework for jointly modeling scene evolution and ego actions in autonomous d

agentsarxiv-cs-cv

Learning to Look Again: Loss-Gap Supervision for Free-form Crop Routing in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2608.21762v1 Announce Type: cross Abstract: Vision-language models (VLMs) fail many detail-centric questions for a concrete reason: the answer is visible in the image, yet lost after the image i

Measuring Stability and Failure Behavior in Language Models Under Structured Perturbations

arXiv:2608.22138v1 Announce Type: new Abstract: Language models are usually judged by a single accuracy score, which does not reveal how their performance degrades as inputs are perturbed. We present

MedReaMM: Evaluating Large Multimodal Models on Expert-Level Clinical Diagnostic Synthesis

arXiv:2608.22323v1 Announce Type: new Abstract: The application of Large Language Models (LLMs) to diagnostic decision-making has garnered growing interest. However, existing benchmarks largely focus

More accurate behavioral predictions with hybrid Bayesian-connectionist models

arXiv:2608.22154v1 Announce Type: new Abstract: Researchers must often choose between Bayesian or neural network models of behavior, two paradigms with complementary strengths and weaknesses. An ideal

TASSO: TAsk-Specific Subspace Optimization for Continual Learning of Vision-Language Models

arXiv:2608.21487v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) exhibit strong zero-shot capabilities, making them an attractive solution for continual learning across diverse tasks. H

// There Is No Neutral Harness // Great work discussing some of the issues in harness evaluation. Twelve open-weight models answer the same …

// There Is No Neutral Harness // Great work discussing some of the issues in harness evaluation. Twelve open-weight models answer the same 3,679 items from ARC, HellaSwag, MMLU, and TruthfulQA under

model-releasesdair-ai--x

Top open models by use case 👇 chat - Kimi K3, Qwen3.8 2.4T A95B reasoning - Kimi K3, DeepSeek V4 Pro coding agents - Kimi K3, DeepSeek V4 F…

model-releasestogether-ai--x

Top open models by use case 👇 chat - Kimi K3, Qwen3.8 2.4T A95B reasoning - Kimi K3, DeepSeek V4 Pro coding agents - Kimi K3, DeepSeek V4 Flash, GLM 5.2 small + fast - Qwen3.8 27B, gpt-oss 20B mid-siz

What Proves You Wrong: Benchmarking Language Models on Falsifiable Research Ideation

arXiv:2608.22948v1 Announce Type: cross Abstract: Large language models are increasingly used to propose research ideas, yet the prevailing ways of judging such ideas supply no shared decision rule: f

Local Ai

Where World Models Break: Natural-Input Failure Discovery

arXiv:2608.22421v1 Announce Type: new Abstract: World models predict action-conditioned futures and serve as critical internal simulators for downstream planning and control. However, catastrophic pre

local-aiarxiv-cs-ai

Can Scientific Claims Be Removed from Large Language Models? A Systematic Evaluation of Claim-Level Unlearning

arXiv:2608.20960v1 Announce Type: new Abstract: Language models (LMs) are trained on static scientific corpora, whereas scientific knowledge continuously evolves through correction and revision. Scien

Large Language Models at the Intersection of Software Engineering and Software Security:An Evidence-Centered Structured Survey and Research Agenda

arXiv:2608.21107v1 Announce Type: new Abstract: Large Language Models (LLMs) are moving from code completion toward repository-scale agents that retrieve context, edit files, execute tools, and partic

Local Ai

ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models

arXiv:2608.21100v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) extend model capabilities beyond text, they also make safety alignment increasingly challenging. Multimod

local-aiarxiv-cs-ai

StateSight: Benchmarking Latent Spatial-State Reconstruction in Vision-Language Models

arXiv:2608.20414v1 Announce Type: new Abstract: Vision-language models are increasingly used for multimodal question answering, yet their ability to reconstruct latent spatial structure from a single

It is not inherently bad to publish research on the impact of AI that only refers to older models, but it requires a very careful discussion…

model-releasesethan-mollick--x

It is not inherently bad to publish research on the impact of AI that only refers to older models, but it requires a very careful discussion and has to be very clear to non-technical readers. If you s

23 Aug 2026

ADAPT: Physics-Aware Diffusion-based World Models for Adaptive Predictive Transferable HVAC Control

arXiv:2608.19804v1 Announce Type: new Abstract: Buildings account for roughly one-third of global energy consumption and CO_2 emissions. Optimizing indoor climate systems plays a critical role for urb

Air Traffic Control Using Large Language Models: Prompt Engineering, Architecture, and Evaluation

arXiv:2608.19299v1 Announce Type: new Abstract: Air traffic control (ATC) communication is a safety-critical dialogue that remains largely human-driven even as other parts of air traffic management ha

Calibrated Triage, Not Autonomy: Confidence Estimation for Medical Vision-Language Models

arXiv:2606.15910v2 Announce Type: replace Abstract: A vision-language model can answer a question about a chest radiograph or a pathology slide fluently and confidently while barely using the image, r

agentsarxiv-cs-cl

Inducing Task Models from Computer-Use Traces

arXiv:2608.20319v1 Announce Type: cross Abstract: Naturalistic computer-use traces, passively recorded screenshots and mouse or keyboard actions, are a valuable resource for deriving symbolic, auditab

agentsarxiv-cs-ai

Reinforcing Egocentric Spatial Perception in Multimodal Large Language Models via Ego Scene Augmentation

arXiv:2607.14497v2 Announce Type: replace Abstract: Egocentric Visual Question Answering (VQA) has attracted widespread attention as an important task for enabling Multimodal Large Language Models (ML

TempJail: Temporal Jailbreak Attack against Large Vision-Language Models via Subtitle Scheduling

arXiv:2608.19737v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have achieved remarkable progress in video understanding and reasoning. Despite extensive studies on text- and im

DeepTCM1.0: A Multi-Expert AI Agent for Deciphering Mechanisms of Chinese Herbal Formulae Based on General Large Language Models

arXiv:2608.18103v1 Announce Type: cross Abstract: Background: Mechanistic elucidation of traditional Chinese medicine (TCM) compound formulas remains a central challenge in the modernization of TCM. C

Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction

arXiv:2512.05092v2 Announce Type: replace-cross Abstract: Although diffusion models now occupy a central place in generative modeling, introductory treatments commonly assume Euclidean data and seldom

GEAR: Generative Expansion and Real Anchoring for Two-Stage Distillation of Tabular Foundation Models

arXiv:2608.18849v1 Announce Type: new Abstract: Tabular foundation models (TFMs) achieve strong performance through in-context learning, but context-dependent inference imposes substantial latency and

GLM-5.3 (Max) by @Zai_org has shifted the Pareto frontier for Code Arena: WebDev! GLM-5.3 (Max) would sit at #2 among open models (upon open…

model-releaseszhipu-ai--x

GLM-5.3 (Max) by @Zai_org has shifted the Pareto frontier for Code Arena: WebDev! GLM-5.3 (Max) would sit at #2 among open models (upon open weights release, and #8 overall) with 1597 pts in the Code

Looped Language Models Improve Compositional Tool Calling

arXiv:2608.18171v1 Announce Type: new Abstract: Looped language models have shown promising results on reasoning benchmarks, yet their potential for agentic tool use remains largely unexplored. We stu

agentsarxiv-cs-ai

Preference Reasoning under Indeterminacy in Large Language Models

arXiv:2608.18631v1 Announce Type: new Abstract: As large language models evolve into decision-making agents, the ability to reason over preferences becomes fundamental to alignment, coordination, and

safetyarxiv-cs-ai

Applications

Sobolev Regularized Score Difference Estimation in Diffusion Models

arXiv:2608.18237v1 Announce Type: cross Abstract: Estimating the difference of two Stein's score functions is a fundamental problem in generative modeling. In particular, score differences arise natur

applicationsarxiv-cs-lg