Search: “models”

MobileWAM: Bridging World Action Models to Mobile Manipulation with Chain-of-Foresight

arXiv:2608.04657v1 Announce Type: new Abstract: World action models (WAMs) built on video generation backbones are a rising recipe for robot learning, yet remain confined to tabletop manipulation. Mob

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Overcoming Statistical Bias in Action-Controllable World Models

DGX agent

arXiv:2608.04653v1 Announce Type: new Abstract: Action-conditioned world models aim to predict how visual environments evolve under an agent's actions. Yet future frames are often highly predictable f

safetyarxiv-cs-cv

6 Aug 2026

Persistent Object Narratives for Token-Efficient Video Language Models

arXiv:2608.04866v1 Announce Type: new Abstract: Video large language models (Video-LLMs) have made strong progress in open-ended video understanding. However, their visual interfaces remain token-inte

Personalized Federated Sparse Adaptation of Time-Series Foundation Models

arXiv:2608.04695v1 Announce Type: cross Abstract: Federated adaptation of time-series foundation models (TSFMs) is attractive for building energy forecasting because meter data are private, distribute

Tutorials

Unforgettable Generalization in Language Models

arXiv:2409.02228v2 Announce Type: replace-cross Abstract: When language models (LMs) are trained to forget (or 'unlearn'') a skill, how precisely does their behavior change? We study the behavior of t

tutorialsarxiv-cs-cl

Adaptive Two-Stage Visual Token Pruning for Efficient Inference in Video-Language Models

arXiv:2608.03112v1 Announce Type: cross Abstract: Vision-language models excel at image and video understanding but suffer from high inference latency due to the need to process thousands of tokens pe

BanglaWild: An In-the-Wild Bengali Scene Text Recognition Benchmark for OCR and Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2608.03884v1 Announce Type: cross Abstract: In-the-wild Bengali scene text recognition is largely unmeasured: existing resources target handwritten documents or constrained sign-board parsing, r

Federated generative event models for tokenized electronic health records

arXiv:2608.02939v1 Announce Type: new Abstract: Electronic health record foundation models are limited by institutionally siloed data and substantial performance degradation under cross-site transfer.

researcharxiv-cs-lg

FOUND-AF: Benchmarking ECG Foundation Models for Atrial Fibrillation Detection

arXiv:2608.03597v1 Announce Type: new Abstract: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with increased risks of stroke, heart failure, and mortality.

researcharxiv-cs-ai

Interpreting Black-Box Large Language Models with Sentence-Level Energy Landscapes

arXiv:2608.02879v1 Announce Type: new Abstract: The widespread adoption of proprietary Large Language Models (LLMs) accessed strictly through closed APIs has created a critical challenge for responsib

local-aiarxiv-cs-ai

Attention-Steered Vision-Language Models for Sign Language Translation

arXiv:2608.00235v1 Announce Type: new Abstract: Vision-language models (VLMs) have emerged as a powerful framework for multimodal video understanding. However, they remain limited in the sign language

CopyCat: Improving Fine-Grained Subject Consistency in Subject-to-Image Models within Seconds

arXiv:2608.00674v1 Announce Type: new Abstract: Recent subject-to-image models have achieved impressive progress in personalized image generation, yet they still struggle to preserve fine-grained subj

Disentangling Visuo-Tactile Foresight: Oracle-Guided Interface Discovery for World Action Models

model-releasesarxiv-cs-ro

arXiv:2608.00547v1 Announce Type: new Abstract: Contact-rich manipulation remains challenging because successful control depends on physical interaction cues that are often weakly observable from visi

Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models

arXiv:2604.01622v2 Announce Type: replace-cross Abstract: Diffusion language models (DLMs) enable parallel, non-autoregressive text generation, yet existing DLM mixture-of-experts (MoE) models inherit

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HAFI-VLM: A Frequency Perspective for Diagnosing and Enhancing Visual Perception in Vision-Language Models

arXiv:2608.02124v1 Announce Type: cross Abstract: Vision-language models (VLMs) remain unreliable when predictions require fine-grained visual evidence. We identify a previously overlooked cause: spec

researcharxiv-cs-cl

IoU-PD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models

arXiv:2607.15732v2 Announce Type: replace Abstract: Visual grounding with multimodal large language models is commonly formulated as autoregressive coordinate generation, where a model outputs boundin

Kilobyte Models: Neural Networks as a Seed and a Quantized Latent

arXiv:2608.00860v1 Announce Type: new Abstract: The cost of storing and transmitting a trained neural network scales with its parameter count, a bottleneck for over-the-air updates, on-device librarie

Leak It: A Probabilistic Approach to Training-Data Extraction from Black-Box Language Models

arXiv:2608.00144v1 Announce Type: cross Abstract: Membership inference (MIA) on language models is usually summarised by an aggregate ROC-AUC, but such evaluations are confounded: model-free blind bas

researcharxiv-cs-cl

MDTD-ArtIR: Benchmarking Image Editing and Restoration Models for Art Image Restoration under Texture-Overlay Degradations

arXiv:2608.00736v1 Announce Type: new Abstract: Restoring severely degraded visual media still remains a formidable challenge, as existing methods often hallucinate unnatural textures and contents, st

Robust Watermarks Meet Backdoored Models: Evading Diffusion Semantic Watermarks via Stealthy Backdoor

arXiv:2608.00543v1 Announce Type: cross Abstract: Although semantic watermarking is considered a promising safeguard for images generated by Latent Diffusion Models (LDMs), the reliance of the waterma

RSVideo: Are Your Vision-Language Models Ready for Remote Sensing Videos?

arXiv:2608.02039v1 Announce Type: new Abstract: Remote-sensing videos enable real-time observation of changes in target attributes, short-term activities, and scene evolution. They record motion, acti

SPECTRA: Band-Routed Embedding and Stage-Wise LoRA for Cross-Sensor Fine-Tuning of Geospatial Foundation Models

arXiv:2608.01751v1 Announce Type: new Abstract: Geospatial foundation models (GeoFMs), pretrained on large-scale geospatial data such as Earth observation (EO), climate, and weather data, have shown p

Structured Memory for Edge Language Models: Persistent Context and Corpus Retrieval via O(1) SSM State Injection

arXiv:2608.02560v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) imposes a prefill cost proportional to retrieved context length, and -- with Transformer backbones -- a KV-cache th

Understanding Synergistic Interactions among Pathology Foundation Models via Adaptive Fusion

arXiv:2608.01370v1 Announce Type: new Abstract: Pathology foundation models (PFMs) provide strong tile-level representations via self-supervised pre-training on large-scale pathology images. Yet, PFMs

CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models

arXiv:2607.28991v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in multimodal understanding and generation. However, when textual inp

Faster but Different: Diagnosing and Controlling Content Drift in Accelerated Multimodal Diffusion Language Models

arXiv:2607.29079v1 Announce Type: new Abstract: Training-free acceleration makes diffusion-based multimodal large language models (dMLLMs) more deployable, but it may silently change generated content

safetyarxiv-cs-cl

In-situ Autoguidance: Eliciting Self-Correction in Diffusion Models

arXiv:2510.17136v2 Announce Type: replace Abstract: The generation of high-quality, diverse, and prompt-aligned images is a central goal in image-generating diffusion models. The popular classifier-fr

safetyarxiv-cs-lg

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models

arXiv:2607.29561v1 Announce Type: cross Abstract: Symbolic Regression (SR) aims to discover analytical equations from observational data and plays a central role in scientific modeling. While recent L

local-aiarxiv-cs-ai

Parameter-Efficient Fine-Tuning for Spiking Point Cloud Models

arXiv:2607.29048v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer energy-efficient solutions for point cloud analysis on resource-constrained devices through event-driven computatio

Reasoning in Real World Clinical Care: Why Large Language Models Are Not Yet Safe for Autonomous Clinical Decision Support

arXiv:2607.28677v1 Announce Type: new Abstract: LLM now pass medical licensing examinations and, in curated cases, can rival physicians at diagnostic reasoning. These developments have accelerated the

safetyarxiv-cs-ai

The Asymmetric Effects of Knowledge Distillation on Bias in Small Language Models

arXiv:2607.28639v1 Announce Type: cross Abstract: We show that knowledge distillation in small instruction-tuned language models has asymmetric effects on bias. On unambiguous tasks (BBQ-disambig), re

Auditing Question-Order Effects in Large Language Models with the QQ Equality: Mechanism Characterization and a Saturation Caveat

model-releasesarxiv-cs-cl

arXiv:2607.17219v2 Announce Type: replace Abstract: Question-order effects in human survey data have been reported to approximately satisfy the QQ (quantum question) equality, a parameter-free predict

31 Jul 2026

LLM2Vec-Gen: Generative Embeddings from Large Language Models

model-releasesarxiv-cs-cl

arXiv:2603.10913v3 Announce Type: replace Abstract: Fine-tuning LLM-based text embedders via contrastive learning maps inputs and outputs into a new representational space, discarding the LLM's output

31 Jul 2026

Position, Not Provenance: Separating Reasoning Mediation from Sycophancy in Medical Vision-Language Models

arXiv:2607.27304v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) generate chain-of-thought (CoT) reasoning before answering clinical questions, but whether this reasoning causal

31 Jul 2026

Anatomy Contextualized Adaption of CT Foundation Models

arXiv:2607.27154v1 Announce Type: new Abstract: CT vision-language foundation models have demonstrated promising performance across downstream tasks, but are typically trained with whole-volume repres

safetyarxiv-cs-cv

Dual Inversion for Text-to-Image Diffusion Models: From Both Prompt and Noise Perspectives

arXiv:2607.26735v1 Announce Type: new Abstract: Prompt inversion, as a typical reverse engineering technique, enables text-to-image (T2I) diffusion models to generate the desired target images without

safetyarxiv-cs-cv

From Found to Designed: Concepts as a Design Axis for Large Language Models

arXiv:2607.26825v1 Announce Type: new Abstract: Large language models (LLMs) encode rich concept-like information, but represent it implicitly through distributed statistical associations rather than

safetyarxiv-cs-cl

Applications

See2Think: Do Multimodal Models Really Use Intermediate Visual States?

arXiv:2607.26769v1 Announce Type: new Abstract: Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reasoning, but it remains unclear whether

applicationsarxiv-cs-cv

Try Again, Don't Look Back: Blind Resampling Outperforms Self-Repair in Small Code Models

arXiv:2607.26117v1 Announce Type: cross Abstract: Self-repair - returning a failed program to the model together with its test output and asking for a correction - is a standard component of code agen

local-aiarxiv-cs-lg

Two Calls Beat Five Agents: Evaluating Multi-Agent Pipelines Against Self-Refinement for Local Language Models

arXiv:2607.26922v1 Announce Type: new Abstract: Multi-agent LLM pipeline systems break down the task among multiple roles for better reasoning, but are benchmarked mainly with large-scale commercial m

What Can Latent World Models Know? Physical Parameter Identifiability in Multimodal Predictive Representations

arXiv:2607.27017v1 Announce Type: new Abstract: A central premise of latent world models is that predicting the future forces a representation to internalize the physics of its environment. Which phys

CaRE Compute-aware Remasking Evaluation Protocol for Masked Diffusion Language Models

arXiv:2607.24763v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) are advancing rapidly, yet the evaluation standards needed to reliably interpret their progress have not kept p

researcharxiv-cs-ai

Applications

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

arXiv:2607.26000v1 Announce Type: cross Abstract: Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to en

applicationsarxiv-cs-ai

GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models

arXiv:2607.24764v1 Announce Type: new Abstract: The rapid growth of online grocery shopping requires recommendation systems that capture cyclical purchasing behavior and diverse user intents. Traditio

Applications

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers

arXiv:2512.17351v2 Announce Type: replace Abstract: Understanding architectural differences in language models is challenging, especially at academic-scale pretraining (e.g., 1.3B parameters, 100B tok

applicationsarxiv-cs-cl

SAM3D-Guided Object-Centric Representation Alignment for Vision-Language-Action Models

arXiv:2607.25912v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for general robot manipulation, but most existing models rely on 2D visual-language ba

local-aiarxiv-cs-ai

Tutorials

VisualPatchWorld: Code World Models as Latent Structured Representations for Planning

arXiv:2607.25236v1 Announce Type: new Abstract: Different research lines use the term world model in different ways, yet they share a common aim: to capture how the world evolves under action in a for

tutorialsarxiv-cs-cl

{au}: Learning Touch-Augmented Vision-Language-Action Models from Future Visual Supervision