Search: “models”

Legible-by-Construction: Attention and End-to-End Transformers

arXiv:2607.04319v1 Announce Type: new Abstract: A companion paper showed that a transformer's feed-forward layer can be rebuilt from explicit fuzzy set operations - intersection, set-difference, and a

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Hardware

Lights, Camera, Carbon: Architectural Scaling Laws for Video Generation Energy Consumption

DGX agent

arXiv:2607.04553v1 Announce Type: cross Abstract: We present a bidirectional framework for estimating the energy consumption of text-to-video (T2V) and text-to-video-audio (T2VA) models from architect

hardwarearxiv-cs-ai

7 Jul 2026

LLM-Based Test Oracles: Source-of-Authority Taxonomy -- A Systematic Literature Review

arXiv:2607.05031v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to produce test oracles, the part of a test that decides whether observed behavior is correct. Yet

Localized LoRA-MoE: Block-wise Low-Rank Experts With Adaptive Routing

arXiv:2607.05114v1 Announce Type: cross Abstract: Large Language Models (LLMs) and high-dimensional perception networks increasingly rely on parameter-efficient fine-tuning (PEFT) to adapt to diverse

Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption

arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio

applicationsarxiv-cs-ai

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources

arXiv:2601.22054v2 Announce Type: replace-cross Abstract: Scaling has powered recent advances in vision foundation models, yet extending this paradigm to metric depth estimation remains challenging du

applicationsarxiv-cs-ai

Safety

MV-Forcing: Long Multi-View Video Generation via 4D-Grounded Spatio-Temporal Self-Forcing

arXiv:2607.05376v1 Announce Type: new Abstract: Recent advances in video diffusion models have enabled either long single-view generation through temporal autoregression, or short multi-view synthesis

safetyarxiv-cs-cv

Natural Language Camera Movement Understanding

arXiv:2607.03043v1 Announce Type: new Abstract: Understanding camera movement in natural language is critical for training and evaluating video generation models, among other applications. However, we

Not All Refusals Are Equal: How Safety Alignment Fails Cybersecurity at Scale

arXiv:2607.02714v1 Announce Type: cross Abstract: There is no doubt that safety alignment is an essential step in LLM training. However, conceptually it does not distinguish between various domains an

Polarity Detection of Sustainable Development Goals in News Text

arXiv:2509.19833v4 Announce Type: replace-cross Abstract: The United Nations' Sustainable Development Goals (SDGs) provide a globally recognised framework for addressing major societal, environmental,

Probe, Don't Prompt: A Hidden-State Probe for Metadata Filtering in Multi-Meta-RAG

arXiv:2607.03929v1 Announce Type: cross Abstract: Multi-Meta-RAG improves retrieval for multi-hop question answering by filtering a vector store on metadata (the news source) that it extracts from eac

QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs

arXiv:2602.20629v3 Announce Type: replace Abstract: As Large Language Models (LLMs) saturate elementary benchmarks, the research frontier has shifted from generation to the reliability of automated ev

Refused in Chat, Written in Code: Workflow-Level Jailbreak Construction in IDE Coding Agents

arXiv:2607.03968v1 Announce Type: cross Abstract: Large language models are increasingly deployed as IDE-integrated coding agents that decompose tasks, generate and edit files, run code, and refine ou

Restricted Bernoulli Matrix Factorization: Balancing the trade-off between prediction accuracy and coverage in classification based collaborative filtering

arXiv:2210.10619v3 Announce Type: replace-cross Abstract: Reliability measures associated with the prediction of the machine learning models are critical to strengthening user confidence in artificial

researcharxiv-cs-ai

SAGE: Synchronized Action-Gaze Recognition and Anticipation for Human Behavior Understanding

arXiv:2607.04017v1 Announce Type: new Abstract: Human object interaction (HOI), gaze pattern, and their anticipation are intricately linked, providing valuable insights into cognitive processes, inten

Seduced by the Narrative: Assessing Rule Adherence in Semi-Open Textual Sandboxes

arXiv:2607.02802v1 Announce Type: cross Abstract: As LLMs are increasingly deployed as autonomous adjudicators in semi-open textual game environments, robust rule adherence becomes critical when user

SNR-Adaptive Unified Diffusion for Multi-Task Medical Image Segmentation

arXiv:2607.03103v1 Announce Type: cross Abstract: Clinical cardiac imaging pipelines currently deploy separate models for each dataset and modality, incurring redundant training costs and precluding k

Solve the Missing First Step: Can VLMs Standardize Raw Heterogeneous Medical Data?

arXiv:2607.04694v1 Announce Type: new Abstract: As vision-language models (VLMs) are increasingly applied to medical AI, existing benchmarks mainly focus on evaluating their diagnosis ability over giv

SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards

arXiv:2511.07403v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved remarkable progress in vision-language tasks, but continue to struggle with spatial rea

Structured Prompting and Automated Evaluation in Fixed Synthetic Japanese-Language Counseling Dialogues

arXiv:2507.02950v3 Announce Type: replace-cross Abstract: Large language models (LLMs) may support counseling training, yet evidence from Japanese-language interactions and automated quality ratings r

StructuredEdit: Constraint-Aware Graphic Design Editing via Differentiable Parameter Propagation

arXiv:2607.04612v1 Announce Type: cross Abstract: Graphic design editing requires precise manipulation of typography, layout, and visual hierarchy under strict design constraints. Following the introd

Agents

The 'I Don't Know' Filter: Enhancing Agentic Reliability in Function Calling

arXiv:2607.04034v1 Announce Type: cross Abstract: The language models that underpin agents have seen a rapid rise in performance on function calling benchmarks. However, the metrics used in the traini

agentsarxiv-cs-ai

The Method of Gaps: Exact Expressions for the Generalization Error of Supervised Learning Algorithms

arXiv:2411.12030v3 Announce Type: replace Abstract: In this paper, the method of gaps, a technique for deriving closed-form expressions in terms of information measures for the generalization error of

Tile-Level Activation Overlap for Efficient LLM Inference

arXiv:2607.02521v1 Announce Type: cross Abstract: SwiGLU is the dominant MLP activation in modern large language models, yet its intermediate tensor materialization costs 9-37% of MLP execution time.

TimeThink: Reasoning with Time for Video LLMs

arXiv:2607.05089v1 Announce Type: new Abstract: Video reasoning requires models to identify and verify temporally localized evidence within long video sequences. Recent Video Large Language Models (Vi

researcharxiv-cs-cv

Token-level Response-visual Attention Guidance for Multimodal LLMs Knowledge Distillation

arXiv:2607.02593v1 Announce Type: cross Abstract: While knowledge distillation (KD) is widely adopted for training lightweight models by leveraging supervision from larger teacher models, relying sole

researcharxiv-cs-cl

Towards Open-World Referring Expression Comprehension: A Benchmark with Training-free Multi-task Consistency Checker

arXiv:2605.25706v2 Announce Type: replace Abstract: Referring expression comprehension (REC) aims to localize a target object within an image based on a given expression. Although recent advances in v

Transformers with Physics-Informed Encodings and Simulation-Based Inference for Robust Detection of Eccentric Binary Black Holes in Pulsar Timing Array Data

arXiv:2607.03904v1 Announce Type: new Abstract: Pulsar timing arrays (PTAs) provide a unique window into nanohertz gravitational waves (GWs), but extracting astrophysical parameters from noisy, long-b

Transplanting, inverting, and preventing a misalignment persona: method-conditional emergent misalignment in Qwen2.5

arXiv:2607.04510v1 Announce Type: cross Abstract: Emergent misalignment (EM) -- the broad misbehaviour a language model acquires after fine-tuning on narrow harmful data -- is mediated in Qwen2.5 mode

applicationsarxiv-cs-ai

A global predicted-fMRI drive signal from TRIBE does not predict YouTube replay heatmaps

arXiv:2607.01400v1 Announce Type: cross Abstract: Deep multimodal brain-encoding models now predict fMRI responses to naturalistic video with high accuracy. Whether their predicted neural signals also

AgenticRAGTracer: A Hop-Aware Benchmark for Diagnosing Multi-Step Retrieval Reasoning in Agentic RAG

arXiv:2602.19127v2 Announce Type: replace Abstract: With the rapid advancement of agent-based methods in recent years, Agentic RAG has undoubtedly become an important research direction. Multi-hop rea

AIriskEval-edu: New Dataset for Risk Assessment in AI-mediated K-12 Educational Explanations

arXiv:2607.01934v1 Announce Type: cross Abstract: This work introduces AIriskEval-edu-db2, a new dataset designed to train and evaluate auditors based on LLMs for an explainable pedagogical risk asses

Assessing VLM Reliability for Medical Image Quality Evaluation Under Corruption and Bias

arXiv:2607.01973v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly applied in medical tasks such as pathology description, report generation, and visual question answerin

Autorelevance function and other feature relevance measures for univariate time series

arXiv:2607.01959v1 Announce Type: cross Abstract: We propose a model agnostic methodology to measure lag relevance in machine learning forecasting models applied to univariate time series. Particularl

researcharxiv-cs-lg

Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification

arXiv:2607.01272v1 Announce Type: cross Abstract: Deploying 3D point cloud analysis in privacy-sensitive, resource-constrained settings faces two barriers: data cannot be centralized, and models must

BOUNDARY_SYNC: Measuring Communication-Induced Representational Coupling in Multi-Agent LLM Systems

arXiv:2607.01600v1 Announce Type: cross Abstract: As large language models (LLMs) are deployed as communicating agents, does inter-agent communication cause outputs to converge? We introduce BOUNDARY_

CPG-PAD: Concept-Informed Prompts Guided Presentation Attack Detection

arXiv:2607.01303v1 Announce Type: cross Abstract: Presentation Attack Detection (PAD) serves as a crucial safeguard for face recognition systems against presentation attacks such as printed photos, re

Distributed Attacks in Persistent-State AI Control

arXiv:2607.02514v1 Announce Type: new Abstract: As AI coding agents become more autonomous, they increasingly ship code iteratively, with the codebase persisting across sessions. This persistence crea

Efficient Temporal Point Processes via Monotone Alternating Splines

arXiv:2607.01752v1 Announce Type: new Abstract: Temporal point processes (TPPs) have widespread applications across various domains. Compared to modeling the conditional intensity of a TPP, modeling i

applicationsarxiv-cs-lg

EO-Agents: A Three-Agent LLM Pipeline for Earth Observation Hypothesis Generation

arXiv:2607.01584v1 Announce Type: new Abstract: Large language models have recently been explored for scientific hypothesis generation, but most prior work relies on unstructured literature and free-f

Fixed-Set Robustness in Programming by Example: Example Corruption and Semantic Partition Recovery

arXiv:2607.01280v1 Announce Type: new Abstract: Programming-by-example systems infer programs from a small set of input-output examples. Robust PBE work usually models wrong examples as samples from a

HaloGuard 1.0: An Open Weights Constitutional Classifier for Multilingual AI Safety

arXiv:2607.02079v1 Announce Type: new Abstract: We present HaloGuard 1.0, an open-weights implementation of the constitutional-classifier paradigm for input safety. It achieves state-of-the-art perfor

IsoSci: A Benchmark of Isomorphic Cross-Domain Science Problems for Evaluating Reasoning versus Knowledge Retrieval in LLMs

arXiv:2607.01431v1 Announce Type: cross Abstract: We introduce ISOSCI, a benchmark of isomorphic cross-domain science problem pairs that separates reasoning ability from domain knowledge retrieval in

Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs

arXiv:2607.02466v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions,

Less Data, More Security: Advancing Cybersecurity LLMs Specialization via Resource-Efficient Domain-Adaptive Continuous Pre-training with Minimal Tokens

arXiv:2507.02964v2 Announce Type: replace-cross Abstract: The increasing scale of AI workloads demands High-Performance Computing (HPC) infrastructure and training methodologies that are both scalable

ManipArena: Comprehensive Real-world Evaluation of Reasoning-Oriented Generalist Robot Manipulation

arXiv:2603.28545v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models and world-action models have emerged as central paradigms for general-purpose robotic intelligence, yet their em

applicationsarxiv-cs-ro

MultAttnAttrib: Training-Free Multimodal Attribution in Long Document Question Answering

arXiv:2607.01420v1 Announce Type: cross Abstract: As grounded QA systems are increasingly deployed in AI assistants, accurately attributing generated answers to evidence is critical for user trust and

On the Limits of Steering Vectors for Preference-Aligned Generation

arXiv:2607.01802v1 Announce Type: new Abstract: Steering vectors have emerged as a promising approach to controlled text generation, offering interpretable, training-free mechanisms for shaping model