Search: “models”

SpecEyes: Accelerating Agentic Multimodal LLMs via Speculative Perception and Planning

arXiv:2603.23483v2 Announce Type: replace-cross Abstract: Agentic multimodal large language models (MLLMs) (e.g., OpenAI o3 and Gemini Agentic Vision) achieve remarkable reasoning capabilities through

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Model Releases

The Moving Target: A Longitudinal Audit of Trustworthiness Drift Across Twelve Checkpoints of Open-Source Chat LLMs

DGX agent

arXiv:2607.02587v1 Announce Type: cross Abstract: Model cards quote trust-benchmark scores without recording when they were measured, and the same number is routinely carried across successive checkpo

model-releasesarxiv-cs-lg

7 Jul 2026

Towards Reliable Local Security Agents: Verifiable Post-Training for Linux Privilege Escalation

arXiv:2603.17673v2 Announce Type: replace-cross Abstract: LLM agents are becoming increasingly important in the security domain, but leading systems are often closed-source, cloud-based, hard to repro

TrendFact: A Benchmark Towards Hotspot Perception in Automatic Fact-Checking

arXiv:2410.15135v5 Announce Type: replace Abstract: With the surge of online misinformation, Large Language Models (LLMs) and Reasoning Large Language Models (RLMs) serving as Automatic Fact-Checking

UniVideo: Unified Understanding, Generation, and Editing for Videos

model-releasesarxiv-cs-cv

arXiv:2510.08377v4 Announce Type: replace Abstract: Unified multimodal models have shown promising results in multimodal content generation and editing but remain largely limited to the image domain.

An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms

arXiv:2603.29466v2 Announce Type: replace-cross Abstract: Existing methods for quantifying predictive uncertainty in neural networks are either computationally intractable for large language models or

Distributionally Robust Listwise Preference Optimization

arXiv:2607.01715v1 Announce Type: new Abstract: Existing robust preference optimization for language-model alignment mainly studies pairwise supervision and places robustness at the dataset, prompt, o

MedStreamBench: A Time-Aware Benchmark for Streaming and Proactive Medical Video Understanding

arXiv:2607.01751v1 Announce Type: cross Abstract: Existing medical video benchmarks primarily evaluate whether a model produces the correct answer, but rarely assess whether it answers at the right ti

Meta-Benchmarks for Financial-Services LLM Evaluation

arXiv:2607.01740v1 Announce Type: new Abstract: Public LLM leaderboards optimise for global average performance and do not capture the specific cognitive demands of financial-services work: a model th

OpenSafeIntent: Evaluating Intent-Calibrated Safe Completion Across Dual-Use Prompt Sets

arXiv:2607.02047v1 Announce Type: cross Abstract: Safe completion requires models to provide useful assistance without enabling harm, but this behavior is difficult to evaluate with isolated prompts.

Scaling with Confidence: Calibrating Confidence of LLMs for Adaptive Test Time Scaling

arXiv:2607.01612v1 Announce Type: new Abstract: Training large language models (LLMs) with reinforcement learning (RL) has significantly advanced their performance on reasoning and question-answering

SCAPE: Accurate and Efficient LLM Training with Extreme Sparse Communication

model-releasesarxiv-cs-lg

arXiv:2607.01678v1 Announce Type: new Abstract: Communication increasingly dominates the cost of Large Language Model (LLM) pre-training, especially under data-parallel and sharded training schemes, w

Continuous Speculative Decoding for Autoregressive Image Generation

arXiv:2411.11925v3 Announce Type: replace Abstract: Continuous visual autoregressive (AR) models have demonstrated promising performance in image generation, but their inherently sequential nature res

safetyarxiv-cs-cv

DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning

arXiv:2607.00341v1 Announce Type: cross Abstract: Large language models achieve strong performance on many reasoning tasks when allowed to externalize intermediate steps as Chain-of-Thought (CoT). How

End-to-End Training for Autoregressive Video Diffusion via Self-Resampling

model-releasesarxiv-cs-cv

arXiv:2512.15702v2 Announce Type: replace Abstract: Autoregressive video diffusion models hold promise for world simulation but are vulnerable to exposure bias arising from the train-test mismatch. Wh

From 'Strings' to 'Things' for Personal Knowledge Graphs: Evaluating LLM Triple Extraction for Recommendation Systems

arXiv:2607.00003v1 Announce Type: cross Abstract: Personal Knowledge Graphs (PKGs) offer a privacy-preserving framework for modeling user preferences, yet constructing them from unstructured, decentra

LLM-Guided ODE Discovery and Parameter Inference from Small-Cohort Aggregate Data

arXiv:2607.00733v1 Announce Type: cross Abstract: Mechanistic modeling via ordinary differential equations (ODEs) provides interpretable descriptions of complex dynamics and enables inference of under

MindEdit-Bench: Benchmarking Object-Level Counterfactual Spatial Reasoning in VLMs from In-the-Wild Photos

arXiv:2607.00491v1 Announce Type: cross Abstract: Benchmarks for vision-language models (VLMs) mostly test observational spatial reasoning: models describe relations already visible in the input. Exis

OmniFall: From Staged Through Synthetic to Wild, A Unified Multi-Domain Dataset for Robust Fall Detection

model-releasesarxiv-cs-cv

arXiv:2505.19889v3 Announce Type: replace Abstract: Visual fall detection models are usually trained on small, staged datasets. Their real-world utility remains unclear; such data lacks diversity and

PHREEQC-MCQ-200: A Diagnostic Benchmark for Tool-Augmented Scientific Simulator Agents

arXiv:2607.00436v1 Announce Type: new Abstract: Large language model agents are increasingly connected to scientific software, yet it remains unclear when tool access makes scientific computation more

Why Advanced Encoders Lag on Sparse Retrieval? The Answer and an Approach to Bridging Vocabulary Gaps

arXiv:2607.00004v1 Announce Type: cross Abstract: While advanced foundation models like ModernBERT significantly outperform older architectures in dense retrieval, they surprisingly lag behind the agi

Amplifying Membership Signal Through Chained Regeneration

arXiv:2606.31991v1 Announce Type: cross Abstract: The tendency of large generative models to memorize training data makes sample verification critical for privacy auditing and copyright enforcement. C

BayesBench: Evaluating LLM Belief Trajectories Under Multi-Turn Evidence Accumulation

arXiv:2606.30850v1 Announce Type: new Abstract: Large language models (LLMs) are typically deployed in multi-turn conversations, where each turn provides new evidence that should reduce epistemic unce

BLUEX v2: Benchmarking LLMs on Open-Ended Questions from Brazilian University Entrance Exams

arXiv:2606.22723v2 Announce Type: replace Abstract: Although Large Language Models (LLMs) excel in many tasks, their assessment in Portuguese has received less attention, particularly for open-ended,

Local Ai

Bridging Local Observation and Global Simulation in Closed-Loop Traffic Modeling

arXiv:2606.31844v1 Announce Type: cross Abstract: A local-to-global context mismatch arises when autoregressive traffic simulators trained on ego-centric driving logs are deployed in globally observab

local-aiarxiv-cs-ai

Applications

CryoACE: An Atom-centric Framework for Accurate and Automated Model Building in Cryo-EM

arXiv:2606.31332v1 Announce Type: new Abstract: Protein automodeling from cryo-EM density maps faces unique challenges in enforcing physicochemical validity and managing conformational heterogeneity.

applicationsarxiv-cs-ai

Applications

Decodable Is Not Grounded: A Vision-Ablation Arbiter for VLM Spatial Reasoning

arXiv:2606.31257v1 Announce Type: new Abstract: The standard way to read latent knowledge out of a model, a linear probe confirmed by a steering recovery, can systematically overstate what a vision-la

applicationsarxiv-cs-cv

ElemeNet: Multiscale Molecular Machine Learning with Uncertainty Quantification Across the Periodic Table

model-releasesarxiv-cs-lg

arXiv:2606.30961v1 Announce Type: cross Abstract: Advances in deep learning architectures and representations have enabled ML-driven chemical property prediction, but state-of-the-art (SOTA) models ha

Layout-Conditioned Autoregressive Text-to-Image Generation via Structured Masking

arXiv:2509.12046v2 Announce Type: replace-cross Abstract: Although autoregressive (AR) models have demonstrated remarkable success in image generation, extending these models to layout-conditioned gen

safetyarxiv-cs-ai

Mind the Residual Gap: Probabilistic Downscaling under Real-World Bias

model-releasesarxiv-cs-lg

arXiv:2606.30821v1 Announce Type: new Abstract: Probabilistic downscaling is the task of modeling the conditional distribution of high-resolution fields given coarse inputs, and is a central challenge

Agents

Reasoning-aware Speculative Decoding for Efficient Vision-Language-Action Models in Autonomous Driving

arXiv:2606.31160v1 Announce Type: new Abstract: Modern Vision-Language-Action (VLA) planners for autonomous driving emit a chain-of-causation (CoC) reasoning step before producing a trajectory. The re

agentsarxiv-cs-cv

Local Ai

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA

arXiv:2606.32002v1 Announce Type: new Abstract: Language models are increasingly taught from synthetic question--answer (QA) supervision: a model generates questions about a document, answers them fro

local-aiarxiv-cs-ai

Stage-Transition Dense Reward Modeling for Reinforcement Learning

arXiv:2606.31377v1 Announce Type: cross Abstract: Reinforcement learning for long-horizon robotic manipulation is often limited by sparse and delayed rewards, while manually designing dense shaping si

Truth or Sophistry? LoFa: A Benchmark for LLM Robustness Against Logical Fallacies

arXiv:2606.31039v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong semantic capabilities, yet their resilience to manipulative linguistic patterns such as logical fallacies re

UniSAE: Unified Speech Attribute Editing on Speaker, Emotion and Low-Level Content via Discrete Phonetic Posteriorgram Modelling

arXiv:2606.31128v1 Announce Type: cross Abstract: Speech editing aims to modify specific portions of an utterance while preserving the remaining speech. Existing approaches primarily focus on word-lev

VIGOR: VIdeo Geometry-Oriented Reward for Temporal Generative Alignment

arXiv:2603.16271v3 Announce Type: replace Abstract: Video diffusion models lack explicit geometric supervision during training, leading to inconsistency artifacts such as object deformation, spatial d

safetyarxiv-cs-cv

Agent-Computer Observation Interfaces Enable Dynamic Computer Use

arXiv:2606.29472v1 Announce Type: new Abstract: SWE-agent established the action interface as an underexplored design axis for software-engineering agents; we make the analogous case for the observati

BERTomelo: Your Portuguese Encoder Best Friend

arXiv:2606.28999v1 Announce Type: cross Abstract: Encoders have become the state of the art for multiple NLP tasks, especially those requiring deep contextual understanding. While multilingual models

Can Fine-Tuning Erase Your Edits? On the Fragile Coexistence of Knowledge Editing and Adaptation

arXiv:2511.05852v4 Announce Type: replace-cross Abstract: Knowledge editing (KE) offers a lightweight alternative to retraining for updating large language models (LLMs). Meanwhile, fine-tuning remain

Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?

arXiv:2606.29920v1 Announce Type: new Abstract: Rubric-based scoring has become a widely used paradigm in model evaluation, typically with LLM-as-a-Judge (LaaJ) for rubric scoring. However, the reliab

Can LLMs Reliably Self-Report Adversarial Prefills, and How?

arXiv:2606.23671v2 Announce Type: replace Abstract: Prior work shows that large language models (LLMs) exhibit introspective capability on benign tasks. We extend the question to safety contexts and e

safetyarxiv-cs-cl

Can OCR-VLMs Read Devanagari? A Stress-Test Benchmark and Post-Correction Study

arXiv:2606.29213v1 Announce Type: new Abstract: OCR systems, ranging from classical engines to specialised OCR vision-language models (OCR-VLMs) and frontier multimodal LLMs, report strong results on

Child-Centric Voice Anonymization in Single and Multi-Speaker Speech via Domain-Adapted SSL Models

arXiv:2606.29897v1 Announce Type: cross Abstract: Voice anonymization aims to protect speaker identity while preserving linguistic content and speech usability. However, most anonymization systems are

Demonstration-Free Robotic Control via LLM Agents

arXiv:2601.20334v2 Announce Type: replace-cross Abstract: Robotic manipulation has increasingly adopted vision-language-action (VLA) models, which achieve strong performance but typically require task

DiffRGD: An Inference-Time Diffusion Guidance Through Riemannian Gradient Descent

arXiv:2606.28417v1 Announce Type: new Abstract: Recently, diffusion models have been widely adopted in generative modeling and have served as foundational models for many image generation tasks. To co

researcharxiv-cs-cv

Diversity is the Strength of the AI Crowd

arXiv:2606.29661v1 Announce Type: new Abstract: Top AI forecasting systems are approaching superforecaster-level accuracy on future world events, but still rely primarily on off-the-shelf LLMs combine

Echoes of Human Malice in Agents: Benchmarking LLMs for Multi-Turn Online Harassment Attacks

arXiv:2510.14207v3 Announce Type: replace Abstract: Large Language Model (LLM) agents are powering a growing share of interactive web applications, yet remain vulnerable to misuse and harm. Prior jail

Emergence of Minimal Circuits for Indirect Object Identification in Attention-Only Transformers

arXiv:2510.25013v2 Announce Type: replace-cross Abstract: Mechanistic interpretability aims to reverse-engineer large language models (LLMs) into human-understandable computational circuits. However,