model releases

Pando: Do Interpretability Methods Work When Models Won't Explain Themselves?

arXiv:2604.11061v1 Announce Type: cross Abstract: Mechanistic interpretability is often motivated for alignment auditing, where a model's verbal explanations can be absent, incomplete, or misleading.

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DGX agent

arXiv:2604.11004v1 Announce Type: cross Abstract: In this work, we introduce a new perspective on comparative image assessment by representing an image pair as a structured composition of its regions.

model-releasesarxiv-cs-ai

14 Apr 2026

PaperScope: A Multi-Modal Multi-Document Benchmark for Agentic Deep Research Across Massive Scientific Papers

arXiv:2604.11307v1 Announce Type: new Abstract: Leveraging Multi-modal Large Language Models (MLLMs) to accelerate frontier scientific research is promising, yet how to rigorously evaluate such system

Para-B&B: Load-Balanced Deterministic Parallelization of Solving MIP

arXiv:2604.09556v1 Announce Type: cross Abstract: Mixed-integer programming (MIP) extends linear programming by incorporating both continuous and integer decision variables, making it widely used in p

Parameter Efficient Fine-tuning for Domain-specific Gastrointestinal Disease Recognition

arXiv:2604.10451v1 Announce Type: new Abstract: Despite recent advancements in the field of medical image analysis with the use of pretrained foundation models, the issue of distribution shifts betwee

ParseBench is the most comprehensive OCR benchmark for real-world enterprise documents: financial filings, contracts, insurance documents, a…

model-releasesjerry-liu--x

ParseBench is the most comprehensive OCR benchmark for real-world enterprise documents: financial filings, contracts, insurance documents, and more. We evaluate across 5 dimensions that are present am

PepBenchmark: A Standardized Benchmark for Peptide Machine Learning

arXiv:2604.10531v1 Announce Type: cross Abstract: Peptide therapeutics are widely regarded as the 'third generation' of drugs, yet progress in peptide Machine Learning (ML) are hindered by the absence

Persona Non Grata: Single-Method Safety Evaluation Is Incomplete for Persona-Imbued LLMs

arXiv:2604.11120v1 Announce Type: new Abstract: Personality imbuing customizes LLM behavior, but safety evaluations almost always study prompt-based personas alone. We show this is incomplete: prompti

PhyMix: Towards Physically Consistent Single-Image 3D Indoor Scene Generation with Implicit--Explicit Optimization

arXiv:2604.10125v1 Announce Type: new Abstract: Existing single-image 3D indoor scene generators often produce results that look visually plausible but fail to obey real-world physics, limiting their

Physics-informed AI Accelerated Retention Analysis of Ferroelectric Vertical NAND: From Day-Scale TCAD to Second-Scale Surrogate Model

arXiv:2603.06881v2 Announce Type: replace-cross Abstract: Ferroelectric field-effect transistors (FeFET)-based vertical NAND (Fe-VNAND) has emerged as a promising candidate to overcome z-scaling limit

Pioneer Agent: Continual Improvement of Small Language Models in Production

arXiv:2604.09791v1 Announce Type: new Abstract: Small language models are attractive for production deployment due to their low cost, fast inference, and ease of specialization. However, adapting them

Playing Along: Learning a Double-Agent Defender for Belief Steering via Theory of Mind

arXiv:2604.11666v1 Announce Type: cross Abstract: As large language models (LLMs) become the engine behind conversational systems, their ability to reason about the intentions and states of their dial

Please Make it Sound like Human: Encoder-Decoder vs. Decoder-Only Transformers for AI-to-Human Text Style Transfer

arXiv:2604.11687v1 Announce Type: new Abstract: AI-generated text has become common in academic and professional writing, prompting research into detection methods. Less studied is the reverse: system

Point2Pose: Occlusion-Recovering 6D Pose Tracking and 3D Reconstruction for Multiple Unknown Objects Via 2D Point Trackers

arXiv:2604.10415v1 Announce Type: new Abstract: We present Point2Pose, a model-free method for causal 6D pose tracking of multiple rigid objects from monocular RGB-D video. Initialized only from spars

PokeRL: Reinforcement Learning for Pokemon Red

model-releasesarxiv-cs-lg

arXiv:2604.10812v1 Announce Type: new Abstract: Pokemon Red is a long-horizon JRPG with sparse rewards, partial observability, and quirky control mechanics that make it a challenging benchmark for rei

Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage

arXiv:2603.23966v3 Announce Type: replace-cross Abstract: With frequently evolving Advanced Persistent Threats (APTs) in cyberspace, traditional security solutions approaches have become inadequate fo

Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation

arXiv:2604.11290v1 Announce Type: new Abstract: Synthesizing supervised finetuning (SFT) data from language models (LMs) to teach smaller models multilingual tasks has become increasingly common. Howe

Powerful Training-Free Membership Inference Against Autoregressive Language Models

arXiv:2601.12104v2 Announce Type: replace-cross Abstract: Fine-tuned language models pose significant privacy risks, as they may memorize and expose sensitive information from their training data. Mem

Precision Synthesis of Multi-Tracer PET via VLM-Modulated Rectified Flow for Stratifying Mild Cognitive Impairment

arXiv:2604.11176v1 Announce Type: new Abstract: The biological definition of Alzheimer's disease (AD) relies on multi-modal neuroimaging, yet the clinical utility of positron emission tomography (PET)

ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models

arXiv:2604.09824v1 Announce Type: cross Abstract: Vision language action (VLA) models enable generalist robotic agents but often exhibit language ignorance, relying on visual shortcuts and remaining i

Progressive Multimodal Interaction Network for Reliable Quantification of Fish Feeding Intensity in Aquaculture

arXiv:2506.14170v3 Announce Type: replace-cross Abstract: Accurate quantification of fish feeding intensity is crucial for precision feeding in aquaculture, as it directly affects feed utilization and

PSF-Med: Measuring and Explaining Paraphrase Sensitivity in Medical Vision Language Models

arXiv:2602.21428v2 Announce Type: replace Abstract: Medical Vision Language Models (VLMs) can change their answers when clinicians rephrase the same question, a failure mode that threatens deployment

Quantitative Introspection in Language Models: Tracking Emotive States Across Conversation

arXiv:2603.18893v2 Announce Type: replace Abstract: Tracking the internal states of large language models across conversations is important for safety, interpretability, and model welfare, yet current

Quantization Dominates Rank Reduction for KV-Cache Compression

arXiv:2604.11501v1 Announce Type: cross Abstract: We compare two strategies for compressing the KV cache in transformer inference: rank reduction (discard dimensions) and quantization (keep all dimens

Radiology Report Generation for Low-Quality X-Ray Images

arXiv:2604.10188v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have significantly advanced automated Radiology Report Generation (RRG). However, existing methods implicitly assume high-

RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time

arXiv:2604.11626v1 Announce Type: new Abstract: Most reward models for visual generation reduce rich human judgments to a single unexplained score, discarding the reasoning that underlies preference.

RCBSF: A Multi-Agent Framework for Automated Contract Revision via Stackelberg Game

arXiv:2604.10740v1 Announce Type: new Abstract: Despite the widespread adoption of Large Language Models (LLMs) in Legal AI, their utility for automated contract revision remains impeded by hallucinat

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search

arXiv:2603.01692v3 Announce Type: replace-cross Abstract: LLM-based agents for machine learning engineering (MLE) predominantly rely on tree search, a form of gradient-free optimization that uses scal

ReContraster: Making Your Posters Stand Out with Regional Contrast

arXiv:2604.10442v1 Announce Type: new Abstract: Effective poster design requires rapidly capturing attention and clearly conveying messages. Inspired by the ``contrast effects'' principle, we propose

Reducing Hallucination in Enterprise AI Workflows via Hybrid Utility Minimum Bayes Risk (HUMBR)

model-releasesarxiv-cs-lg

arXiv:2604.11141v1 Announce Type: new Abstract: Although LLMs drive automation, it is critical to ensure immense consideration for high-stakes enterprise workflows such as those involving legal matter

ReFEree: Reference-Free and Fine-Grained Method for Evaluating Factual Consistency in Real-World Code Summarization

arXiv:2604.10520v1 Announce Type: cross Abstract: As Large Language Models (LLMs) have become capable of generating long and descriptive code summaries, accurate and reliable evaluation of factual con

Relational Preference Encoding in Looped Transformer Internal States

arXiv:2604.09870v1 Announce Type: cross Abstract: We investigate how looped transformers encode human preference in their internal iteration states. Using Ouro-2.6B-Thinking, a 2.6B-parameter looped t

Relax: An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale

arXiv:2604.11554v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training has proven effective at unlocking reasoning, self-reflection, and tool-use capabilities in large language mode

ReplicateAnyScene: Zero-Shot Video-to-3D Composition via Textual-Visual-Spatial Alignment

arXiv:2604.10789v1 Announce Type: new Abstract: Humans exhibit an innate capacity to rapidly perceive and segment objects from video observations, and even mentally assemble them into structured 3D sc

Respondology launches Respond to turn comments into competitive advantage

model-releasessiliconangle

Respondology, the provider of a social media comment moderation and intelligence platform, today announced the launch of Respond, an artificial intelligence-powered platform that engages with social m

Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation

arXiv:2604.10397v1 Announce Type: cross Abstract: Video-based human-object interaction (HOI) understanding requires both detecting ongoing interactions and anticipating their future evolution. However

Retrieval-Augmented Large Language Models for Evidence-Informed Guidance on Cannabidiol Use in Older Adults

arXiv:2604.09548v1 Announce Type: cross Abstract: Older adults commonly experience chronic conditions such as pain and sleep disturbances and may consider cannabidiol for symptom management. Safe use

Revisiting the Scale Loss Function and Gaussian-Shape Convolution for Infrared Small Target Detection

arXiv:2604.09991v1 Announce Type: new Abstract: Infrared small target detection still faces two persistent challenges: training instability from non-monotonic scale loss functions, and inadequate spat

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

arXiv:2604.10916v1 Announce Type: cross Abstract: Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-language models (VLMs) could enable autonomous ultrasound

Rhizome OS-1: Rhizome's Semi-Autonomous Operating System for Small Molecule Drug Discovery

arXiv:2604.07512v2 Announce Type: replace Abstract: We present Rhizome OS-1, a semi-autonomous operating system for small molecule drug discovery in which multi-modal AI agents operate as a full multi

RISK: A Framework for GUI Agents in E-commerce Risk Management

arXiv:2509.21982v2 Announce Type: replace Abstract: E-commerce risk management requires aggregating diverse, deeply embedded web data through multi-step, stateful interactions, which traditional scrap

RiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs in Medicine

arXiv:2410.13987v3 Announce Type: replace Abstract: Answering complex real-world questions in the medical domain often requires accurate retrieval from medical Textual Knowledge Graphs (medical TKGs),

RL-Driven Sustainable Land-Use Allocation for the Lake Malawi Basin

arXiv:2604.03768v2 Announce Type: replace Abstract: Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This pap

RL makes MLLMs see better than SFT

arXiv:2510.16333v2 Announce Type: replace Abstract: A dominant assumption in Multimodal Language Model (MLLM) research is that its performance is largely inherited from the LLM backbone, given its imm

RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies

arXiv:2604.09860v1 Announce Type: cross Abstract: The pursuit of general-purpose robotics has yielded impressive foundation models, yet simulation-based benchmarking remains a bottleneck due to rapid

Robust Adversarial Policy Optimization Under Dynamics Uncertainty

model-releasesarxiv-cs-lg

arXiv:2604.10974v1 Announce Type: new Abstract: Reinforcement learning (RL) policies often fail under dynamics that differ from training, a gap not fully addressed by domain randomization or existing

Robust Fair Disease Diagnosis in CT Images

arXiv:2604.09710v1 Announce Type: new Abstract: Automated diagnosis from chest CT has improved considerably with deep learning, but models trained on skewed datasets tend to perform unevenly across pa

RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation

arXiv:2604.09814v1 Announce Type: new Abstract: Medical image segmentation models built on Segment Anything Model (SAM) achieve strong performance on clean benchmarks, yet their reliability often degr