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Beyond Blind Compliance: Benchmarking Task Verification in OCR Reasoning

arXiv:2609.00232v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved strong performance on OCR-centric document understanding and text-rich visual reasoning benchmark

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Tutorials

Beyond Landmark Extraction: A Framework for Robust Geometric Feature Construction in Structured Image Classification

DGX agent

arXiv:2609.00634v1 Announce Type: new Abstract: Much of the literature on structured image recognition has disproportionately focused on the comparison of classification algorithms. Rather than invest

tutorialsarxiv-cs-cv

2 Sept 2026

Beyond Language Priors: Diagnosing and Fixing Visual-Origin Hallucinations in Multimodal LLM

arXiv:2609.00231v1 Announce Type: new Abstract: Existing research on object hallucination in multimodal large language models (MLLMs) predominantly attributes the problem to language priors such as ov

Beyond Magnitude: Contrastive Routing for Modular Mixture-of-Experts

arXiv:2609.01100v1 Announce Type: new Abstract: In current Mixture-of-Experts architectures, routing is performed based on representations dominated by structure shared across all tokens, limiting exp

researcharxiv-cs-cl

Beyond Object Selection:Markerless Gaze-based Robot Placement at Arbitrary Position

model-releasesarxiv-cs-ro

arXiv:2609.00478v1 Announce Type: new Abstract: Gaze-based assistive manipulation typically supports object selection, while arbitrary-position placement requires accurate spatial alignment between th

Beyond Scores: Understanding LLM-as-a-Judge Mechanisms in Summarization Evaluation

arXiv:2609.01604v1 Announce Type: new Abstract: LLM-based evaluators of natural language generation (NLG) quality are widely deployed as scoring tools and as automated training signals, yet the intern

Beyond Static Summarization: Proactive Memory Extraction for LLM Agents

arXiv:2601.04463v2 Announce Type: replace-cross Abstract: Memory management is vital for LLM agents in long-term and personalized interactions. Most previous work studies how to retrieve and use memor

agentsarxiv-cs-ai

Beyond the Clock: Measuring the Value of Adaptive Revision

arXiv:2609.00874v1 Announce Type: new Abstract: As agentic systems become compound systems, increasingly important decisions move above task execution itself: when should a higher-level controller pre

Beyond the Image Plane: World-Grounded Queries for Multi-Object Tracking

arXiv:2609.00924v1 Announce Type: cross Abstract: Monocular videos record 3D scenes as sequences of 2D image-plane projections, obscuring depth and spatial relationships. Multi-object trackers localiz

Beyond Token Positions: Safety Alignment Across Denoising Steps in Diffusion Language Models

arXiv:2609.00495v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising rather than left-to-right decoding. This generation paradigm introdu

Beyond Tokens: Semantic-Aware Speculative Decoding for Efficient Inference by Probing Internal States

arXiv:2602.03708v3 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance across many tasks but suffer from high inference latency due to autoregressive decoding. The

researcharxiv-cs-cl

BiasGym: A Simple and Generalizable Framework for Analyzing and Removing Biases through Injection

arXiv:2508.08855v5 Announce Type: replace-cross Abstract: Understanding biases and stereotypes encoded in the weights of Large Language Models (LLMs) is crucial for developing effective mitigation str

BinWalker: Development and Field Evaluation of a Quadruped Manipulator Platform for Sustainable Litter Collection

arXiv:2603.10529v2 Announce Type: replace Abstract: Litter pollution represents a growing environmental problem affecting natural and urban ecosystems worldwide. Waste discarded in public spaces often

agentsarxiv-cs-ro

Births are difficult to predict even with rich survey and full-population register data

arXiv:2609.01194v1 Announce Type: new Abstract: Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine on

researcharxiv-cs-lg

BrainDiff: Longitudinal Report Generation for Multimodal Brain MRI

arXiv:2609.00593v1 Announce Type: new Abstract: Neuroradiologists rarely read a brain MRI in isolation, yet automated brain-MRI report generation has been built almost entirely for single studies. Tem

Breaking the Structural Identity: Personalized Federated LoRA Fine-tuning under Rank Heterogeneity

arXiv:2609.00632v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable success across diverse domains, but their adaptation to privacy-sensitive, distributed datasets

Bridging Lexical Divergence: LLM-Assisted, Cost-Efficient, Zero-shot Scientific Entity Linking

arXiv:2609.00228v1 Announce Type: new Abstract: Scientific domain entity linking (EL) differs from general domain EL because mentions and entity names often lack lexical overlap. Another challenge is

BS: Take the Hint - Interactive Multitracer PET/CT Lesion Segmentation with a Scribble-Conditioned ResEnc U-Net

arXiv:2609.01554v1 Announce Type: cross Abstract: Automated lesion segmentation in whole-body PET/CT is complicated by the variety of physiological tracer uptake patterns and by the differing appearan

Tutorials

Building Expressive and Tractable Probabilistic Generative Models: A Review

arXiv:2402.00759v4 Announce Type: replace-cross Abstract: We present a comprehensive survey of the advancements and techniques in the field of tractable probabilistic generative modeling, primarily fo

tutorialsarxiv-cs-ai

C-DiffSET: Leveraging Latent Diffusion for SAR-to-EO Image Translation with Confidence-Guided Reliable Object Generation

arXiv:2411.10788v4 Announce Type: replace Abstract: Synthetic Aperture Radar (SAR) imagery provides robust environmental and temporal coverage (e.g., during clouds, seasons, day-night cycles), yet its

Hardware

CacheBridge: Efficient Cross-Model KV Cache Transfer

arXiv:2609.00891v1 Announce Type: new Abstract: Sharing context between LLMs in a multi-model system requires the receiving model to prefill the shared prefix because KV caches are model-specific. Rec

hardwarearxiv-cs-ai

Applications

CADKnitter: Compositional CAD Generation from Text and Geometry Guidance

arXiv:2512.11199v2 Announce Type: replace Abstract: Computer-aided design (CAD) defines 3D models as compact, precise, and editable representations, making it directly useful for several fields. Recen

applicationsarxiv-cs-cv

Calibration is the Bottleneck: An Action-Class Diagnostic of Multi-Turn Tool-Calling

arXiv:2609.00949v1 Announce Type: cross Abstract: Multi-turn tool calling is a core evaluation scenario for large language model (LLM) agents. On public tool-calling benchmarks, open-weight models now

CameraEditor: Camera-Controlled Image Editing via Video-Prior Sequential Modeling

arXiv:2609.01479v1 Announce Type: new Abstract: Beyond semantic content, camera parameters play a pivotal role in dictating the geometric perspective and appearance of any given image. While recent im

Can Large Language Models Forecast What Researchers Study Next?

arXiv:2609.00747v1 Announce Type: new Abstract: Large language models increasingly generate research ideas, yet judging their novelty or feasibility at generation time does not establish whether they

Can LLMs Design Video Coding Tools? A Case Study on Planar Mode

arXiv:2609.01535v1 Announce Type: cross Abstract: This paper explores whether large language models (LLMs) can design video coding tools, a highly challenging task due to the intricate algorithmic cou

Can LLMs Discover Scientific Laws in Real and Parallel Worlds?

arXiv:2609.01552v1 Announce Type: new Abstract: Scientific equation discovery has long been central to scientific progress, proceeding through iterative cycles of hypothesis generation, observational

Can LLMs Use Relational Transformer Embeddings?

arXiv:2609.00457v1 Announce Type: new Abstract: Injecting frozen relational-encoder embeddings as soft tokens into a large language model (LLM) is a conceptually appealing fusion strategy: the encoder

safetyarxiv-cs-lg

Can machines think efficiently?

arXiv:2510.26954v3 Announce Type: replace-cross Abstract: The Turing Test is no longer adequate for distinguishing human and machine intelligence. With advanced artificial intelligence systems already

Can Scene Text Recognition Read Rare Compositions?

arXiv:2609.00816v1 Announce Type: new Abstract: Scene text recognition is reported as 89--97% accurate on the six standard benchmarks, and the problem is widely treated as saturated. We present an alt

Candidate-Expanding Routing with Permutation-Stabilized Experts for Mixed-Format Medical VQA

arXiv:2609.00959v1 Announce Type: new Abstract: Mixed-format medical visual question answering (VQA) requires stable option selection and machine-readable free-text output. The two formats fail differ

Capability-Gated Language Models: Security Composes, Utility Does Not

arXiv:2609.00445v1 Announce Type: cross Abstract: Deployed language model safeguards (safety fine-tuning, filtering, unlearning) vary by principal only outside the model weights: filters are reconfigu

CARE: Contrastive Anchor-based Rubric Evolution for Large Language Model Post-Training

arXiv:2609.00892v1 Announce Type: new Abstract: Rubric-based reinforcement learning decomposes open-ended instructions into prompt-specific, flexible rubrics, making it better suited than reinforcemen

CaRL-EM: Cost-Aware Reinforcement Learning for Entity Matching with LLMs

arXiv:2609.01195v1 Announce Type: new Abstract: Entity matching (EM) requires fine-grained contextual understanding and domain knowledge. Recent work shows that large language models (LLMs) can serve

safetyarxiv-cs-cl

CATeye: Coupled Attribute-Topology Invariance Learning for Voucher Abuse Detection

model-releasesarxiv-cs-lg

arXiv:2609.01425v1 Announce Type: new Abstract: Voucher abuse poses a major challenge in e-commerce, where malicious users exploit promotional vouchers for profit. Unfortunately, fraud patterns evolve

Causal Evidentiary Governance for High-Risk Machine Learning Systems

arXiv:2609.01040v1 Announce Type: cross Abstract: Machine learning systems deployed for credit, hiring, and resource distribution are increasingly subject to regulatory oversight from policies such as

Causal Probing for Internal Visual Representations in Multimodal Large Language Models

arXiv:2605.05593v2 Announce Type: replace Abstract: Despite the remarkable success of Multimodal Large Language Models (MLLMs) across diverse tasks, the internal mechanisms governing how they encode a

CERF: Communication-Efficient and Retraining-Free Collaborative Perception

arXiv:2609.00951v1 Announce Type: new Abstract: Collaborative perception shares information among multiple agents to obtain a comprehensive scene representation, enhancing the perceptual capability of

agentsarxiv-cs-cv

Channel-Adaptive Edge AI: Maximizing Inference Throughput by Adapting Computational Complexity to Channel States

arXiv:2603.03146v2 Announce Type: replace-cross Abstract: Integrated communication and computation (IC^2) has emerged as a new paradigm for enabling efficient edge inference in sixth-generation (6G) n

CHARM: Character Hallucination for Multicultural Role Play Benchmark

arXiv:2609.01352v1 Announce Type: cross Abstract: Role-playing large language models (LLMs) are expected to adopt a character's style while also respecting that character's knowledge boundaries. Prior

ChatDev 2.0: A No-Code Multi-Agent Platform for Developing Everything

arXiv:2609.00714v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) have shown strong potential for solving complex tasks, yet their development forces a tradeof

agentsarxiv-cs-ai

Cheap Verifiers, Large Blind Spots: Measuring the Reliability Cost of Cost-Saving Cascades

arXiv:2609.01345v1 Announce Type: new Abstract: Inference cascades cut cost by answering most queries with a cheap model and escalating a hard tail to a frontier model that acts as verifier. A natural

Citing Less Critically: LLMs Reshape the Rhetoric and Reach of Scientific Citation

arXiv:2609.01432v1 Announce Type: cross Abstract: Scientific citations carry rhetorical intent. Scholars may cite prior work positively (supporting), negatively (contrasting), or neutrally (mentioning

safetyarxiv-cs-cl

Applications

Cleaner Speech, Weaker Generalization: Revisiting Pitt-Derived Benchmarks for Alzheimer's Disease Detection

arXiv:2609.00276v1 Announce Type: cross Abstract: Speech-based Alzheimer's disease (AD) detection increasingly relies on speech-enhanced and curated versions of the Pitt Corpus, where speech enhanceme

applicationsarxiv-cs-ai

ClinTraceBench: Source-Verifiable Longitudinal Clinical Reasoning over EHR-Derived Dialogues

arXiv:2609.01111v1 Announce Type: new Abstract: Clinical LLM assistants must reason over multi-visit patient trajectories, yet whether the compact history representations used to scale them---retrieva

Hardware

Closing Cost-Quality Gap in Document VLMs: Difficulty-Aware Data Curation and Quality-Adjusted Deployment Economics

arXiv:2609.01575v1 Announce Type: new Abstract: Extracting structured fields from hundreds of millions of documents annually remains costly in regulated industries: bespoke OCR cascades cover only a f

hardwarearxiv-cs-cl

CMRVision: A Foundation Model for Cardiac MR Image Analysis

arXiv:2609.01308v1 Announce Type: new Abstract: Cardiac magnetic resonance (CMR) imaging provides complementary information on cardiac anatomy, function, and tissue characterization across multiple se

CoBRA: Learning Tool-Use Boundaries via Counterfactual Margins

arXiv:2609.00967v1 Announce Type: new Abstract: As large language models increasingly act through external tools, deciding when to call a tool has become a central problem alongside deciding how to us

agentsarxiv-cs-ai