Search: “models”

WOLF-VLA: Whole-Body Humanoid Optimal Locomotion Framework for Vision-Language-Action Learning

model-releasesarxiv-cs-ro

arXiv:2606.25591v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently demonstrated strong generalization in robotic manipulation, yet their applicability to whole-body, con

25 Jun 2026

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

Deep Learning Approaches for 3D Medical Scene Completion: From Geometric Modeling to Generative Paradigms

DGX agent

arXiv:2606.24180v1 Announce Type: cross Abstract: Three-dimensional scene completion has evolved as a major problem in computer vision and robotics, and its applications are diverse, including autonom

agentsarxiv-cs-ai

24 Jun 2026

EG-VQA: Benchmarking Verifiable Video Question Answering with Grounded Temporal Evidence

arXiv:2606.24797v1 Announce Type: cross Abstract: Recent advances in Video Large Language Models (Video-LLMs) have yielded promising performance on video question answering (VideoQA). Nevertheless, ex

EgoSAT: A Comprehensive Benchmark of Egocentric Streaming Interaction Understanding

arXiv:2606.24422v1 Announce Type: new Abstract: We introduce EgoSAT, the first comprehensive benchmark for egocentric video reasoning in streaming settings, designed to evaluate the capabilities of mo

Local Ai

ESBMC-GraphPLC: Formal Verification of Graphical PLCopen XML Ladder Diagram Programs Using SMT-Based Model Checking

arXiv:2606.18941v3 Announce Type: replace-cross Abstract: PLCopen XML defines two encoding formats for IEC 61131-3 Ladder Diagram programs: a textual encoding using elements, and a graphical encoding

local-aiarxiv-cs-cl

IPO Finance Agent: Evaluation of LLM Financial Analysts beyond Finance Agent v2, with Automated Rubric Generation -- the Case of the SpaceX (SPCX) IPO

arXiv:2606.23032v2 Announce Type: replace Abstract: Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language model

Legal Reasoning Is Not Lawyering: Rethinking Legal Benchmarks for Pro Se Access to Justice

arXiv:2606.23716v1 Announce Type: cross Abstract: Legal AI benchmark research frequently invokes the assumption that large language models can improve access to justice, including for people who canno

LemonHarness Technical Report

arXiv:2606.24311v1 Announce Type: new Abstract: As large language model (LLM) agents are applied to longer tasks, they increasingly modify workspace state across multiple rounds of iteration. However,

ParaPairAudioBench: Paralinguistic Pairwise Audio Benchmark for LALM-as-a-Judge

arXiv:2606.24648v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have been widely used as judge models for the automatic evaluation of generated speech. However, prior approaches

Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs

arXiv:2511.20892v4 Announce Type: replace Abstract: Large language models (LLMs) often produce incorrect or outdated content after being employed. Efficient and accurate knowledge updates without cost

Agents

Thinking While Speaking: Inference-Time Knowledge Transfer for Responsive and Intelligent Conversational Voice Agents

arXiv:2511.07397v2 Announce Type: replace Abstract: Voice agents face a fundamental tension: the reasoning, retrieval, and tool use that make foundation models capable are iterative and slow, while co

agentsarxiv-cs-cl

To Compare, or Not to Compare: On Methodological Practices in Evaluating Social Bias

arXiv:2606.24596v1 Announce Type: new Abstract: As Large Language Models are increasingly deployed in critical applications, robustly evaluating their social biases is paramount. However, the current

TrOCR for Medieval HTR: A Systematic Ablation Study with Cross-Dataset Validation

arXiv:2606.24302v1 Announce Type: new Abstract: Fine-tuning transformer-based handwritten text recognition (HTR) models on medieval manuscripts is challenging because these models are pre-trained on m

UniDrive: A Unified Vision-Language and Grounding Framework for Interpretable Risk Understanding in Autonomous Driving

arXiv:2606.24759v1 Announce Type: cross Abstract: Recent multimodal large language models (MLLMs) have shown strong potential for autonomous driving scene understanding, yet existing methods still fac

VeriPilot: An LLM-Powered Verilog Debugging Framework

arXiv:2606.23759v1 Announce Type: cross Abstract: Verilog debugging remains one of the most time-consuming stages in digital circuit design. Recent advances in Large Language Models (LLMs) have enable

video-SALMONN-R^3: Learning to ReWatch, ReAsk, and ReAnswer for Efficient Video Understanding

arXiv:2606.24477v1 Announce Type: cross Abstract: Video large language models (LLMs) are often constrained by computation and memory budgets, leading them to use reduced frame rates and spatial resolu

Agents

Vision-Language Model Reasoning for Contextual Semantic Mapping in Intralogistics

arXiv:2606.24814v1 Announce Type: new Abstract: Autonomous mobile robots operating in intralogistics environments rely on geometric maps for localization and navigation, but lack semantic understandin

agentsarxiv-cs-ro

AgentMisalignment: Measuring the Propensity for Misaligned Behaviour in LLM-Based Agents

arXiv:2506.04018v3 Announce Type: replace-cross Abstract: As Large Language Model (LLM) agents become more widespread, associated misalignment risks increase. While prior research has studied agents'

Safety

ALOE: Action-Level Off-Policy Evaluation for Vision-Language-Action Model Post-Training

arXiv:2602.12691v3 Announce Type: replace Abstract: We study how to improve large foundation vision-language-action (VLA) systems through human-in-the-loop reinforcement learning (RL) in real-world en

safetyarxiv-cs-ro

Research

An Empirical Study of OpenPangu Quantization on Ascend NPUs

arXiv:2606.21257v1 Announce Type: new Abstract: OpenPangu models are attractive targets for private and domestic large-language-model deployment, yet their robustness under aggressive post-training qu

researcharxiv-cs-lg

Safety

BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation

arXiv:2606.23531v1 Announce Type: new Abstract: Endoscopic retrograde cholangiopancreatography (ERCP) demands precise endoscopic navigation and stable biliary cannulation within a narrow monocular fie

safetyarxiv-cs-ro

Research

DevoTG: Temporal Graph Neural Networks for Modeling C. elegans Developmental Connectomics

arXiv:2606.21940v1 Announce Type: new Abstract: Understanding how a nervous system wires itself from birth to adulthood is a fundamental challenge in developmental neuroscience. We present DevoTG, a t

researcharxiv-cs-lg

Evaluating and Enhancing Negation Comprehension in Remote Sensing MLLMs

arXiv:2606.20177v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in various Remote Sensing (RS) tasks. However, their ability to compre

Research

Fine-Grained Uncertainty Quantification for Long-Form Language Model Outputs: A Comparative Study

arXiv:2602.17431v2 Announce Type: replace-cross Abstract: Uncertainty quantification has emerged as an effective approach to closed-book hallucination detection for LLMs, but existing methods are larg

researcharxiv-cs-lg

From Point Estimates to Distributions: GMM Pooling for MIL in Preterm Birth Prediction

arXiv:2606.23005v1 Announce Type: new Abstract: Preterm birth (PTB) prediction can enable targeted surveillance and timely intervention, yet most ultrasound-based models use a single selected transvag

From Speech to Text Corpora: Evaluating ASR-Based Data Acquisition for Low-Resource Fongbe and Hausa

arXiv:2606.22274v1 Announce Type: cross Abstract: Low-resource African languages lack text corpora needed for language model training. We investigate whether ASR pipelines can extend text resources fo

GitOfThoughts: Version-Controlled Reasoning and Agent Memory You Can Replay, Diff, and Merge

arXiv:2606.14470v2 Announce Type: replace-cross Abstract: Large language model reasoning leaves no trace once it is done. The steps of a chain of thought disappear when the context window closes, a pr

Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving

arXiv:2606.22913v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving by incorporating reasoning for better interpretability and planni

Applications

Physics-Informed Modeling for Wood Thermal Analysis and Prediction

arXiv:2606.23402v1 Announce Type: new Abstract: Wood materials exhibit complex, spatially varying thermal properties that challenge traditional architectural assumptions of material homogeneity. Altho

applicationsarxiv-cs-lg

Tutorials

Shared infrastructure, isolated tenants: Pool model multi-tenancy with Amazon Bedrock AgentCore

In this post, you will learn patterns for implementing production-ready multi-tenant systems using Amazon Bedrock AgentCore. You will see these patterns demonstrated through healthcare AI agents that

tutorialsaws-ml-blog

Small LLMs: Pruning vs. Training from Scratch

arXiv:2606.14150v2 Announce Type: replace Abstract: Pruning promises a shortcut to strong small language models. In this work, we examine this promise by pruning Llama-3.1-8B at pruning ratios of 0.5-

Temporal Graph Pattern Machine

arXiv:2601.22454v3 Announce Type: replace Abstract: Temporal graph learning is pivotal for deciphering dynamic systems, where the core challenge lies in explicitly modeling the underlying evolving pat

The Geometry of Refusal: Linear Instability in Safety-Aligned LLMs

arXiv:2606.22686v1 Announce Type: cross Abstract: Modern Large Language Models (LLMs) rely on extensive safety alignment, yet the mechanistic basis of refusal remains opaque. In this work, we investig

Local Ai

Ideogram making 2 horrible precedent and we need to oppose that. BF16 weights not published and ridiculous model embedded censorship

local-air-stablediffusion

I cannot provide a factual summary for a knowledge base without accessing the actual content. Reddit post titles often contain subjective language and don't reliably convey the full argument. To creat

21 Jun 2026

Tutorials

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal

arXiv:2606.12360v1 Announce Type: new Abstract: Language-model post-training is the main stage at which model behavior is shaped, yet it still largely involves optimization of scalar rewards that summ

tutorialsarxiv-cs-lg

Every Act Has Its Price: Compressed Moral Composition in Frontier LLMs

arXiv:2606.11232v1 Announce Type: cross Abstract: Existing LLM moral benchmarks usually ask which isolated moral act, value, or foundation a model prefers. This is useful but incomplete. Realistic jud

Hubs or Fringes: Pretraining Data Selection via Web Graph Centrality

arXiv:2606.11499v1 Announce Type: cross Abstract: The performance of modern language models depends critically on pretraining data composition. Yet existing data selection methods rely on auxiliary cl

LatticeBridge: Rare-Event Sequential Inference for Faithful Structured Sequence Synthesis

arXiv:2606.11203v1 Announce Type: new Abstract: Structured sequence generation often requires a model to satisfy several input-derived constraints in a single output. Standard decoding methods may ass

LLMpedia: A Transparent Framework to Materialize an LLM's Encyclopedic Knowledge at Scale

arXiv:2603.24080v2 Announce Type: replace Abstract: Benchmarks like MMLU suggest flagship language models approach factuality saturation above 90%. LLMpedia shows this picture is incomplete. We materi

Agents

When More Documents Hurt RAG: Mitigating Vector Search Dilution with Domain-Scoped, Model-Agnostic Retrieval

arXiv:2606.11350v1 Announce Type: new Abstract: Retrieval-augmented generation degrades when scaled to large, heterogeneous document collections, where dense similarity loses discriminative power, and

agentsarxiv-cs-cl

BenSyc: Benchmarking Conversational Sycophancy and Human Alignment in LLMs for Bengali Contexts

arXiv:2606.10061v1 Announce Type: new Abstract: Large language models (LLMs) increasingly participate in emotionally sensitive social conversations, where responses may shift from balanced support tow

Bittensor Agent Arenas as a Trajectory Primitive: Distilling a Shopping Agent from ShoppingBench Subnet Traces

arXiv:2606.10064v1 Announce Type: cross Abstract: Small-model agentic post-training is bottlenecked less by the algorithm than by the trajectory substrate it consumes. Leading recipes (RLVR, group-rel

Claude Fable won’t answer basic biology questions

model-releasesthe-verge-ai

Anthropic just released Claude Fable 5, calling it the most powerful AI model it has ever made widely available and praising its skills in biology, among others. But the model won't answer basic biolo

CLP: Collocation-Length Prediction for Zero-Loss Adaptive Multi-Token Inference

arXiv:2606.10935v1 Announce Type: cross Abstract: Large language model inference is bottlenecked by autoregressive decoding, where each token requires a full forward pass. Multi-token prediction (MTP)

Continual LLM Upcycling: A Predictor-Gated Bank-Wise Sparsity Training Recipe for Dense-to-Sparse LLMs

arXiv:2606.10722v1 Announce Type: new Abstract: We study dense-to-sparse continual training as a way to construct channel-sparse large language models from dense checkpoints. Starting from a Qwen2.5-8

Disjoint or Overlapping? Inference Windowing for Reconstruction-Based Time Series Anomaly Detection

arXiv:2606.09874v1 Announce Type: new Abstract: Reconstruction-based methods are widely used for time series anomaly detection, where models are trained to reconstruct subsequences, and anomalies are

Don't waste SAM

arXiv:2606.10696v1 Announce Type: new Abstract: Meta AI has recently released the Segment Anything Model (SAM), which demonstrates exceptional zero-shot image segmentation performance across various t

Efficient RWKV-based Representation Learning for 3D Point Clouds

arXiv:2606.10395v1 Announce Type: new Abstract: The recent receptance weighted key value (RWKV) model combines RNN-style recurrence, offering a linear-complexity alternative to Transformers' quadratic