Search: “models”

ReasoningShield: Safety Detection over Reasoning Traces of Large Reasoning Models

arXiv:2505.17244v3 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) leverage explicit reasoning traces, known as Chain-of-Thought (CoT) reasoning, to decompose complex problems int

12 Oct 2026

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Benefits of using bigger models than Qwen 3.8 flash next?

DGX agent

I recently started using local LLM for mostly coding tasks for my personal projects. I also have found local models responding much better for topics such as health, fitness, ergonomics etc. compared

model-releasesr-localllama

10 Oct 2026

Research

Bernoulli Flow Models: Self-Consistent Generative Modeling for Binary Data

arXiv:2610.11362v1 Announce Type: cross Abstract: Binary diffusion models typically require a large number of function evaluations (NFEs) to generate high-quality samples, making practical inference c

researcharxiv-cs-cv

9 Oct 2026

Hardware

Language Models as AI Research World Models

arXiv:2610.12235v1 Announce Type: new Abstract: AI research agents automate the cycle of proposing, implementing, and evaluating experiments, opening a path toward recursive self-improvement. Yet thei

hardwarearxiv-cs-cl

9 Oct 2026

Quad-State Safety Evaluation of Open-Weight Large Language Models on Non-Canonical Inputs

arXiv:2610.09033v1 Announce Type: new Abstract: Standard safety evaluations of large language models assess harmful requests written in canonical plain text, while models in real-world deployment rout

8 Oct 2026

b11477: llama: share the nextn tensor flags between models (#30097)

model-releasesllama-cpp-releases

llama: share the nextn tensor flags between models Follow-up of the TODO in glm5-next: move the trunk-only and MTP-only detection that each model copied into a nextn_flags helper of llama_model_base.

Research

Finding the Heads and the Neurons Responsible for Network Information Retrieval in Language Models

arXiv:2610.08200v1 Announce Type: new Abstract: We ask whether specific attention heads, and more finely specific neurons inside those heads, are responsible for recognizing that a language model's co

researcharxiv-cs-lg

Local Ai

OpenWAM: An Open Framework for Composable World-Action Models

arXiv:2610.07922v1 Announce Type: cross Abstract: World-action models (WAMs) couple future prediction with robot control, yet existing systems often vary the video backbone, interaction structure, sup

local-aiarxiv-cs-cv

Thin Evidence, Thick Priors: How Language Models Substitute Identity for Missing Financial Facts

arXiv:2610.07798v1 Announce Type: new Abstract: People increasingly ask large language models what to do with their money, yet seldom describe their finances in full. This paper asks what a model does

ALoDLM: Adaptively Looped Diffusion Language Models

arXiv:2610.04198v1 Announce Type: cross Abstract: Diffusion language models (DLMs) enable fast generation by predicting multiple tokens in parallel, but their practical adoption remains limited by a p

FairRSFM: A Biome-Aware Benchmark and Debiasing Framework for Remote Sensing Foundation Models

arXiv:2610.05790v1 Announce Type: new Abstract: Remote sensing foundation models (RSFMs) are commonly evaluated using aggregate metrics, which can hide systematic performance disparities across ecolog

SUAVE: Unified Video-Action Models via Masked Diffusion

arXiv:2610.04009v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) inherit strong semantic grounding from pretrained vision-language backbones but are typically optimized for predi

safetyarxiv-cs-cv

TAPDreamer: Transferable Adversarial Patches for World Action Models

arXiv:2610.06814v1 Announce Type: new Abstract: World models learn to predict how their environment will evolve, making them an important foundation for general-purpose robotic control. Yet world acti

Evaluating and Improving the Robustness of Large Language Models to Input Sequence Variations

arXiv:2610.02432v1 Announce Type: cross Abstract: Large language models (LLMs) in production systems face prompt injections, trojans (backdoors), and manipulation of automatic quality metrics. This th

From Retrieval to Typed Decisions: Calibrated System One Models from Biomedical Sentence Encoders

arXiv:2610.02486v1 Announce Type: cross Abstract: Typed decision models answer schema-constrained questions about a text in one forward pass and return probabilities meant to be thresholded. We ask wh

Keeping JEPA World Models Plannable When Little of the Frame Moves

arXiv:2610.03137v1 Announce Type: new Abstract: Specifying a goal in language rather than as a goal frame is a natural interface for planning with a latent world model, but testing it needs scenes in

Agents

Peer Influence across Heterogeneous AI Models

arXiv:2610.03095v1 Announce Type: new Abstract: When two AI agents disagree, who persuades whom? As multi-agent systems increasingly combine language models of different families and sizes, the answer

agentsarxiv-cs-ai

Agents

CtrlWAM: Controllable World Action Models with Aligned Intent and Foresight

arXiv:2610.00859v1 Announce Type: new Abstract: World action models (WAMs) jointly predict actions (intent) and visual future (foresight). Standard training adds noise to recorded actions and video si

agentsarxiv-cs-cv

Research

How Divergence Becomes Decision Flips in Compressed Language Models

arXiv:2610.00694v1 Announce Type: cross Abstract: Compression reports summarize how far a compressed language model moved from the dense one, usually by a KL divergence; a deployment that relies on th

researcharxiv-cs-ai

Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models

arXiv:2603.16065v3 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has shown strong potential for improving robotic manipulation policies, yet its practical use remains bottlenecked

safetyarxiv-cs-ai

Legal text classification in Korean sexual offense cases: from traditional machine learning to large language models with XAI insights

arXiv:2610.00087v1 Announce Type: cross Abstract: The advancement of natural language processing (NLP) has expanded AI-based text classification in the legal domain. However, accurately classifying le

Network World Models as Environments for Algorithm Design on Complex Systems

arXiv:2610.01048v1 Announce Type: new Abstract: World models, which simulate an environment and predict how it changes under actions, are increasingly used in real-world applications such as robotics.

Reputation, Strategy, and Emotion Effects on Generative AI Cooperation: A Comparison Across Reasoning and Non-Reasoning Models

arXiv:2610.01222v1 Announce Type: new Abstract: As generative AI (Gen AI) systems take on increasingly autonomous roles in economically and socially consequential interactions, understanding their pro

CAST: Causal Advantage-Structured Training with Spatially Grounded Compositional Rewards for Diffusion Models

arXiv:2609.39441v1 Announce Type: cross Abstract: Online reinforcement learning has been extended to flow matching for diffusion model (DM) image generation. However, this paradigm faces three limitat

1 Oct 2026

Grounding Time-Series Foundation Models in Digital Twin Topology for Predictive Maintenance

arXiv:2609.40071v1 Announce Type: cross Abstract: Digital twins increasingly support downstream analytical tasks that depend on time-series data, motivating interest in time-series foundation models (

1 Oct 2026

Understanding as No-Arbitrage: Bounded Dutch Books as a Definition and Training Objective for Language Models

arXiv:2609.39341v1 Announce Type: new Abstract: Does a language model merely predict tokens, or does it understand what it says? We make this question measurable by defining 'understanding' through th

1 Oct 2026

BiasReducer: Adaptive Bias Mitigation for Reward Models

arXiv:2609.32720v1 Announce Type: new Abstract: Reward models score responses from large language models (LLMs) and guide LLM training toward human preferences. However, reward models can favor superf

safetyarxiv-cs-lg

29 Sept 2026

Nudgeability: Reasoning Models Follow Confidence Signals Without Tracking Their Own Competence

arXiv:2609.34572v1 Announce Type: cross Abstract: Reasoning language models that can call tools must decide during inference whether to answer unaided or delegate. Any self-reflection mechanism for th

29 Sept 2026

CCRV-Bench: Constraint-Based Evaluation of Causal Reasoning in Vision-Language Models

arXiv:2609.30979v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated excellent performance in visual tasks, but their visual causal reasoning capabilities still lack reliabl

28 Sept 2026

JevAdvBench: A Benchmark and Black-Box Attacks for Reinforcement Learning for Calibrated Decisions Models

arXiv:2609.31142v1 Announce Type: cross Abstract: Models trained with reinforcement learning for calibrated decisions (RLCD), such as Jev, answer a typed question about an input, the state, with a pro

28 Sept 2026

Pay attention to System One models if you are building custom harnesses and agentic workflows. Great to see DSPy integrate Jev and now suppo…

Pay attention to System One models if you are building custom harnesses and agentic workflows. Great to see DSPy integrate Jev and now support System One models for calibrating agentic workflows. I'm

model-releasesdair-ai--x

25 Sept 2026

Can Vision-Language Models Analyze Human-Centered Video? Mapping Model Capabilities and Human-AI Collaborative Workflows

arXiv:2609.27327v1 Announce Type: new Abstract: Video provides a rich record of human behavior, interaction, and situated contexts, offering important evidence for understanding people and conducting

24 Sept 2026

Scaling of Capability and Efficiency at Inference Time in Large Reasoning Models

arXiv:2609.27166v1 Announce Type: new Abstract: Capability and efficiency are two key dimensions of reasoning in large language models (LLMs). Capability refers to the ability to solve a given problem

24 Sept 2026

Chronologic: Measuring Language Models' Ability to Represent the Past

arXiv:2609.23178v1 Announce Type: new Abstract: Language models are appealing tools for research on the past. But to trust the evidence a model provides, researchers need to know whether its responses

22 Sept 2026

Validating, Not Sampling: Region-Level Robustness of Vision-Language and Vision-Language-Action Models

arXiv:2609.22293v1 Announce Type: new Abstract: Vision-language models (VLMs) and vision-language-action models (VLAs) are increasingly deployed in real-world applications. There, a small perturbation

22 Sept 2026

Learning Surrogate LPV State-Space Models with Uncertainty Quantification

arXiv:2603.29532v2 Announce Type: replace-cross Abstract: The Linear Parameter-Varying (LPV) framework enables the construction of surrogate models of complex nonlinear and high-dimensional systems, f

21 Sept 2026

The Communication Bottleneck: A Round-Trip Study of Tree-Structured Expression Serialization in Language Models

arXiv:2609.21509v1 Announce Type: new Abstract: When language models reason in chain-of-thought or exchange free-text intermediates, they serialize structured information into natural language. How mu

21 Sept 2026

Stress Tests REVEAL Fragile Temporal and Visual Grounding in Video-Language Models

arXiv:2602.11244v2 Announce Type: replace Abstract: Video-Language Models (VidLMs) achieve strong benchmark scores, yet these scores often hide whether models use the video at all. We show that VidLM

18 Sept 2026

Local Ai

AgenTeeth: A Model-Agnostic Framework for Suppressing Hallucination in Frozen Vision-Language Models on Dental X-Rays via Tool Evidence Injection

arXiv:2609.17800v1 Announce Type: new Abstract: Vision-language models (VLMs) remain largely unreliable on panoramic dental radiographs and can rely on learned anatomical priors rather than evidence i

local-aiarxiv-cs-cv

Beyond Routine Compliance: Cunning Data Cultivates Safety Vigilance in Large Language Models

arXiv:2609.18515v1 Announce Type: new Abstract: Safety alignment teaches large language models (LLMs) to recognize harmful requests and reject risky instructions. Yet aligned models can fail when harm

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

Rethinking Domain Specialization for Open-Ended Scientific Reasoning in Astronomy Language Models

arXiv:2609.17644v1 Announce Type: cross Abstract: Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: w

WordPolo: Evaluating Language Models Through Iterative Semantic Feedback

arXiv:2609.19006v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Large Reasoning Models (LRMs) are typically evaluated on challenging benchmarks through dataset accuracy alone, provi

R3: Robust Rubric-Agnostic Reward Models

arXiv:2505.13388v4 Announce Type: replace-cross Abstract: Reward models are essential for aligning language model outputs with human preferences, yet existing approaches often lack both controllabilit

safetyarxiv-cs-ai

16 Sept 2026

Inherited Heads: Audio language models track speakers with their text backbone's attention, and an attention-mass ranking retrieves a different set

arXiv:2609.14174v1 Announce Type: cross Abstract: Asked to describe what one of six speakers in a recording talks about, audio language models describe the right one on 6 to 16% of trials, below the 1

15 Sept 2026

Mirror, Mirror on the Wall: Prompt Echoing in Small Instruct Language Models

arXiv:2609.15045v1 Announce Type: cross Abstract: Prompt echoing is a recognized failure mode of instruct language models, in which a model instead of generating a response, mirrors the provided promp

15 Sept 2026

Local Ai

Hierarchical Prototype Emergence in Modern Hopfield Models

arXiv:2609.12079v1 Announce Type: cross Abstract: Hierarchical correlations are a universal feature of any realistic model of data, and the question of how associative memory models may learn these co

local-aiarxiv-cs-lg

14 Sept 2026

Context operations to architecture modelling output from large language models and evaluation criteria for their use in systems engineering design