Search: “models”

Can Video World Models Track Unobserved World States?

arXiv:2608.30692v1 Announce Type: new Abstract: Video world models are increasingly used as simulators, yet visual fidelity alone does not show that a model maintains the hidden state of the world. We

researcharxiv-cs-cv

Capability-Stratified Degradation in Ternary Language Models

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DGX agent

arXiv:2608.28809v1 Announce Type: new Abstract: Extreme low-bit inference offers a route toward smaller models and constrained deployment. Ternary language models restrict weights to {-1,0,+1}, approa

researcharxiv-cs-ai

1 Sept 2026

Agents

Chat-Edit-3D++: Interactive 3D and 4D Scene Editing via Large Language Models

arXiv:2608.29137v1 Announce Type: new Abstract: Recent work on image content manipulation based on vision-language pre-training models has been effectively extended to text-driven 3D scene editing. Ho

agentsarxiv-cs-cv

Dense Clinical Contrasts Enhance Medical Knowledge Updating in Large Language Models

arXiv:2608.30405v1 Announce Type: new Abstract: Medical knowledge changes continually, making large language models vulnerable to relying on outdated yet clinically plausible information. We study whe

Error Detection for PET/CT Radiology Reports: Domain-Specific vs Large Language Models

arXiv:2608.30021v1 Announce Type: cross Abstract: Errors in radiology reports can adversely affect patient treatment, yet automated report quality assurance remains challenging because errors are ofte

Generative vs. Encoder Models for Multilingual NER: A Comprehensive Empirical Study on Naamapadam

arXiv:2608.29959v1 Announce Type: new Abstract: Language is humanity's most consequential technology, yet for over a billion speakers across India's twenty-two constitutionally recognised languages, i

Matrix-Game 3.5: Enhancing Real-Time Streaming Interactive World Models with Patch Memory

arXiv:2608.29910v1 Announce Type: new Abstract: Interactive world models extend video generation from offline clip synthesis toward persistent simulation of interactive virtual worlds, enabling applic

researcharxiv-cs-cv

Amortizing intractable inference in diffusion models for vision, language, and control

arXiv:2405.20971v3 Announce Type: replace-cross Abstract: Diffusion models have emerged as effective distribution estimators in vision, language, and reinforcement learning, but their use as priors in

researcharxiv-cs-cv

31 Aug 2026

CompareBench: A Benchmark for Visual Comparison Reasoning in Vision-Language Models

arXiv:2509.22737v3 Announce Type: replace Abstract: Visual comparison reasoning is a fundamental capability of vision-language models (VLMs), covering judgments of object quantity, geometric dimension

31 Aug 2026

A Layer Importance Metric for Quantization Accounting for the Speed-Quality Trade-off in Autoregressive Models

arXiv:2608.26926v1 Announce Type: new Abstract: Small language models (sLLMs) are nowadays hosted on devices with limited memory and computational budget. In an autoregressive setup, inference is memo

Are Large Language Models Effective Knowledge Graph Constructors?

arXiv:2510.11297v2 Announce Type: replace Abstract: Knowledge graphs (KGs) are widely used in knowledge-intensive applications, yet it remains unclear how effectively current large language models (LL

Benchmarking Clinical Decision Pathway Adherence in Large Language Models

arXiv:2608.26592v1 Announce Type: new Abstract: Following clinical decision pathways (CDPs) defined by clinical practice guidelines is essential for safe and reliable medical decision-making. However,

Fine-Tuning of Transformer models with Frames

arXiv:2608.26430v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) strategies such as Low-Rank Adaptation (LoRA) are effective solutions for fine-tuning large-scale pre-trained mod

GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts

arXiv:2509.25160v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a key capability for vision-language models (VLMs), yet current benchmarks mainly evaluate text-based or explicitly

Temporally-Grounded Language Generation: Towards Real-Time Vision-Language Models

arXiv:2505.11326v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown remarkable progress in offline tasks such as image captioning and video question answering. However,

When Is Noise Response Universal? Tokenization as the Hidden Variable in Language Models

arXiv:2608.26319v1 Announce Type: new Abstract: The performance of textual neural models often degrades when their inputs are corrupted by noise such as typos, OCR errors, or dropped words. We study t

DCGC: Draft-Conditioned Global Correction for Complex Reasoning with Masked Diffusion Models

arXiv:2608.25428v1 Announce Type: new Abstract: Correcting flawed reasoning traces remains a significant challenge for Large Language Models (LLMs), whose autoregressive generation can propagate early

27 Aug 2026

One Form to Transfer Them All: Pretraining Multilingual Language Models Beyond Native Orthography

arXiv:2608.25904v1 Announce Type: new Abstract: Multilingual language models transfer knowledge across languages through shared subword vocabulary, a mechanism that breaks down when related languages

27 Aug 2026

Latent Action as Intention Enables Efficient Future Imagination for World Action Models

model-releasesarxiv-cs-ro

arXiv:2608.24882v1 Announce Type: new Abstract: World action models (WAMs) improve robot control by modeling how observations evolve, but generating future observations at test time incurs substantial

26 Aug 2026

Local Ai

AgentWeave: Routing Before Reasoning for Efficient Function Calling in Tool-Rich Language Models

arXiv:2608.23078v1 Announce Type: new Abstract: Large language models increasingly operate over large collections of tools, functions, APIs, and specialized agents. As the candidate action space grows

local-aiarxiv-cs-ai

Beyond Benchmarking: Scenario-Based Evaluation of Large Language Models for Personalized Learning

arXiv:2509.05346v3 Announce Type: replace Abstract: While large language models (LLMs) are increasingly being adopted to support personalized learning, there remains limited understanding of how their

Beyond What Meets the Eye: Unveiling Situational Illusions for Multimodal Large Language Models

arXiv:2608.22232v1 Announce Type: new Abstract: Real-world situation appearances can deviate from their underlying physical states, challenging the reliability of multimodal large language models (MLL

Applications

Deep Contrastive Unlearning for Language Models

arXiv:2503.14900v2 Announce Type: replace-cross Abstract: The past a few years have witnessed the great success of large language models, demonstrating powerful capabilities in comprehending textual d

applicationsarxiv-cs-ai

DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning

arXiv:2603.16459v2 Announce Type: replace Abstract: Diffusion large language models (D-LLMs) have emerged as a promising alternative to auto-regressive models due to their iterative refinement capabil

TEE-X: TEE-aware Acceleration Framework for Large Vision Models at the Edge

arXiv:2608.22716v1 Announce Type: cross Abstract: Despite their remarkable success, machine learning models, particularly in vision applications, are alarmingly vulnerable to a range of security threa

safetyarxiv-cs-ai

What's the Catch? Evaluating Temporal Consistency in Vision-Language Models

arXiv:2608.23474v1 Announce Type: cross Abstract: Vision-language models (VLMs) achieve strong performance on video and image-sequence benchmarks, yet it remains unclear whether they capture temporal

COEC: Calibrated Orthogonal-Equivalence Compensation for Structured Pruning of Large Language Models

arXiv:2608.21142v1 Announce Type: new Abstract: Structured pruning reduces the size and inference cost of large language models (LLMs) by removing weight columns, but the resulting output error can de

Detecting Functional Memorization in Code Language Models

arXiv:2606.12764v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to generate code at scale. Meanwhile, prior work has investigated whether training data may

Radiometric fingerprinting of object surfaces using mobile laser scanning and semantic 3D road space models

arXiv:2603.11252v2 Announce Type: replace Abstract: Although semantic 3D city models are internationally available and becoming increasingly detailed, the incorporation of material information remains

RARE: Decoupling Representation Steering from Expert Routing in Mixture-of-Experts Language Models

arXiv:2608.21236v1 Announce Type: new Abstract: Representation engineering offers a lightweight means of controlling language-model behavior by modifying intermediate hidden states, but its direct app

RISE: Adaptive Imagination for World Action Models

arXiv:2608.20430v1 Announce Type: new Abstract: World Action Models (WAMs) improve planning by incorporating future world evolution into action generation, yet existing methods allocate a fixed imagin

safetyarxiv-cs-cv

Smart Exploration in Reinforcement Learning using Bounded Uncertainty Models

arXiv:2504.05978v4 Announce Type: replace Abstract: Reinforcement learning (RL) is a powerful framework for decision-making in uncertain environments, but it often requires large amounts of data to le

Agents

An Irreducible Quantum Advantage in Aligning World Models with Reality

arXiv:2608.19779v1 Announce Type: cross Abstract: World models provide digital simulacra of the true world, allowing agents to be trained and tested before costly real-world deployment. At each time s

agentsarxiv-cs-ai

21 Aug 2026

DiverValue-Bench: A Benchmark and Fine-Tuning Framework for Aligning Large Language Models with Diverse Human Values

arXiv:2509.08022v3 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) with diverse human values is essential for safe and effective deployment, yet existing benchmarks often

21 Aug 2026

Time-Series Retrieval for Grounding Multimodal Language Models in Remaining Useful Life

arXiv:2608.19218v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are increasingly being explored for domain-specific maintenance and prognostics tasks, raising the

21 Aug 2026

Corrections of Zipf's and Heaps' Laws Derived from Hapax Rate Models

arXiv:2307.12896v5 Announce Type: replace Abstract: The article introduces corrections to Zipf's and Heaps' laws based on systematic models of the proportion of hapaxes, i.e., words that occur once. T

Decision-Metric Alignment in Latent World Models: Diagnostics and Action-Conditioned Objectives for MPC Planning

arXiv:2608.18746v1 Announce Type: cross Abstract: JEPA-style latent world models can use Euclidean distance to a goal latent as the cost for model-predictive control (MPC). Strong decoding of task var

safetyarxiv-cs-cv

Million-scale multimodal pollen microscopy with expert-guided foundation models

arXiv:2606.17809v2 Announce Type: replace Abstract: Automated pollen identification from microscopy remains a bottleneck in aerobiology, palaeoecology and biodiversity monitoring, because scalable sys

Hardware

SMTrap: Cost-Effective DoS Attacks Against Large Reasoning Models via SMT Conflict Guidance

arXiv:2608.18921v1 Announce Type: cross Abstract: Existing LRM-DoS methods rely heavily on model feedback to synthesize attack queries, requiring either repeated queries to the target model or trainin

hardwarearxiv-cs-ai

The Embodiment Gap in Robot Foundation Models

arXiv:2608.18433v1 Announce Type: new Abstract: Robot foundation models (RFMs), including vision-language-action (VLA) policies, are often discussed through a scaling view: more data, larger models, a

researcharxiv-cs-ro

Benchmarking Classical and Transformer-Based Models for Document Sensitivity Classification

arXiv:2608.16928v1 Announce Type: new Abstract: Automatic sensitivity classification of organizational documents is a critical yet underserved problem, where the consequences of misclassification rang

19 Aug 2026

Where a New Concept Must Enter: Entry Point Gates Cross-Task Usability in Unified Multimodal Models

arXiv:2608.17564v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) are motivated by the hope that understanding and generation reinforce each other but controlled ablations repeatedly

safetyarxiv-cs-ai

19 Aug 2026

A Comprehensive Survey of Wireless Foundation Models for AI-Native 6G Networks

arXiv:2608.14694v1 Announce Type: new Abstract: Foundation models are emerging as a transformative paradigm for AI-native sixth-generation (6G) wireless networks by enabling scalable, transferable, an

AlignJEPA: Predictive Vision-Language Alignment for Remote Sensing Foundation Models

arXiv:2608.15456v1 Announce Type: new Abstract: Remote sensing (RS) foundation models provide transferable Earth observation representations across sensors, resolutions, and geographies, yet most rema

Architecture-Dependent Causal Transfer of Activation States Across Large Language Models

arXiv:2608.16347v1 Announce Type: new Abstract: Direct communication between AI systems relies on natural language as an intermediate layer, incurring encoding/decoding overhead, token cost, and laten

Certifying Compressed Language Models: An Audit and a Statistical Toolkit

arXiv:2608.15046v1 Announce Type: new Abstract: A fraction of a point of benchmark accuracy is the usual evidence that a compressed model is equivalent to its original. That quantity is least informat

Earth Observation Foundation Models for Terrestrial Ecohydrology: From Representation Learning to Process Inference

arXiv:2608.15282v1 Announce Type: cross Abstract: Earth observation foundation models (EOFMs) are emerging as reusable representation frameworks for data-driven retrieval, prediction and process model

Language Models that Think, Chat Better

arXiv:2509.20357v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) trains language models to use long chain-of-thought reasoning (CoT) in domains like mathematic