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REALM: Reliable Expertise-Aware Language Model Fine-Tuning from Noisy Annotations

arXiv:2604.17289v1 Announce Type: new Abstract: Supervised fine-tuning of large language models relies on human-annotated data, yet annotation pipelines routinely involve multiple crowdworkers of hete

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ReasonEmbed: Enhanced Text Embeddings for Reasoning-Intensive Document Retrieval

DGX agent

arXiv:2510.08252v2 Announce Type: replace-cross Abstract: In this paper, we introduce ReasonEmbed, a novel text embedding model developed for reasoning-intensive document retrieval. Our work includes

model-releasesarxiv-cs-cl

21 Apr 2026

Reasoning Models Know What's Important, and Encode It in Their Activations

arXiv:2604.18307v1 Announce Type: new Abstract: Language models often solve complex tasks by generating long reasoning chains, consisting of many steps with varying importance. While some steps are cr

researcharxiv-cs-cl

Reasoning on the Manifold: Bidirectional Consistency for Self-Verification in Diffusion Language Models

arXiv:2604.16565v1 Announce Type: new Abstract: While Diffusion Large Language Models (dLLMs) offer structural advantages for global planning, efficiently verifying that they arrive at correct answers

safetyarxiv-cs-lg

ReasoningBank: Enabling agents to learn from experience

ReasoningBank is a memory framework that distills generalizable reasoning strategies from an agent's successful and failed experiences, which the agent retrieves at test time to inform interactions wh

tutorialsgoogle-research

ReCap: Lightweight Referential Grounding for Coherent Story Visualization

model-releasesarxiv-cs-cv

arXiv:2604.18575v1 Announce Type: new Abstract: Story Visualization aims to generate a sequence of images that faithfully depicts a textual narrative that preserve character identity, spatial configur

Recent books from the MIT community

Priority Technologies: Ensuring US Security and Shared ProsperityEdited by Elisabeth B. Reynolds, professor of the practice of urban studies and planning and former executive director of the MIT Task

researchmit-tech-review

Reciprocal Co-Training (RCT): Coupling Gradient-Based and Non-Differentiable Models via Reinforcement Learning

arXiv:2604.16378v1 Announce Type: new Abstract: Large language models (LLMs) and classical machine learning methods offer complementary strengths for predictive modeling, yet their fundamentally diffe

tutorialsarxiv-cs-cl

Applications

ReconVLA: An Uncertainty-Guided and Failure-Aware Vision-Language-Action Framework for Robotic Control

arXiv:2604.16677v1 Announce Type: new Abstract: Vision-language-action (VLA) models have emerged as generalist robotic controllers capable of mapping visual observations and natural language instructi

applicationsarxiv-cs-ro

ReCoQA: A Benchmark for Tool-Augmented and Multi-Step Reasoning in Real Estate Question and Answering

arXiv:2604.17944v1 Announce Type: new Abstract: Developing agents capable of navigating fragmented, multi-source information remains challenging, primarily due to the scarcity of benchmarks reflecting

Recovery Guarantees for Continual Learning of Dependent Tasks: Memory, Data-Dependent Regularization, and Data-Dependent Weights

arXiv:2604.17578v1 Announce Type: new Abstract: Continual learning (CL) is concerned with learning multiple tasks sequentially without forgetting previously learned tasks. Despite substantial empirica

Reducing Peak Memory Usage for Modern Multimodal Large Language Model Pipelines

arXiv:2604.16734v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have recently demonstrated strong capabilities in understanding and generating responses from diverse visual in

Reference-state System Reliability method for scalable uncertainty quantification of coherent systems

arXiv:2604.17066v1 Announce Type: new Abstract: Coherent systems are representative of many practical applications, ranging from infrastructure networks to supply chains. Probabilistic evaluation of s

Refinement of Accelerated Demonstrations via Incremental Iterative Reference Learning Control for Fast Contact-Rich Imitation Learning

arXiv:2604.16850v1 Announce Type: new Abstract: Fast execution of contact-rich manipulation is critical for practical deployment, yet providing fast demonstrations for imitation learning (IL) remains

researcharxiv-cs-ro

RefineStat: Efficient Exploration for Probabilistic Program Synthesis

arXiv:2509.01082v3 Announce Type: replace Abstract: Probabilistic programming offers a powerful framework for modeling uncertainty, yet statistical model discovery in this domain entails navigating an

ReFineVLA: Multimodal Reasoning-Aware Generalist Robotic Policies via Teacher-Guided Fine-Tuning

model-releasesarxiv-cs-cv

arXiv:2604.17800v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have gained much attention from the research community thanks to their strength in translating multimodal observat

Applications

REFLEX: Reference-Free Evaluation of Log Summarization via Large Language Model Judgment

arXiv:2511.07458v2 Announce Type: replace Abstract: Evaluating log summarization systems is challenging due to the lack of high-quality reference summaries and the limitations of existing metrics like

applicationsarxiv-cs-cl

REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control

arXiv:2511.20233v3 Announce Type: replace Abstract: The prevalence of fake news on social media demands automated fact-checking systems to provide accurate verdicts with faithful explanations. However

ReflexiCoder: Teaching Large Language Models to Self-Reflect on Generated Code and Self-Correct It via Reinforcement Learning

arXiv:2603.05863v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have revolutionized code generation, standard ``System 1'' approaches that generate solutions in a single forward

Local Ai

Refocus IC LoRA for LTX 2.3 Brings out-of-focus footage back into clarity. This LoRA was created by @MedOumoumad To try this workflow, link …

Refocus IC LoRA is a specialized AI model addon for LTX 2.3 that uses machine learning to restore clarity to out-of-focus video footage. Created by @MedOumoumad, it integrates with the ComfyUI workflo

local-aicomfyui--x

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction

arXiv:2506.01770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In

safetyarxiv-cs-lg

Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging

arXiv:2604.17222v1 Announce Type: new Abstract: Breast cancer diagnosis demands rapid and precise tools, yet traditional histopathological methods often fall short in intra-operative settings. Deep Ul

Local Ai

Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework

arXiv:2604.18145v1 Announce Type: new Abstract: Automated medical report generation for 3D PET/CT imaging is fundamentally challenged by the high-dimensional nature of volumetric data and a critical s

local-aiarxiv-cs-cv

Reinforced Efficient Reasoning via Semantically Diverse Exploration

arXiv:2601.05053v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has proven effective in enhancing the reasoning of large language models (LLMs). Monte C

Agents

Relative State Estimation using Event-Based Propeller Sensing

arXiv:2604.18289v1 Announce Type: cross Abstract: Autonomous swarms of multi-Unmanned Aerial Vehicle (UAV) system requires an accurate and fast relative state estimation. Although monocular frame-base

agentsarxiv-cs-cv

Reliability-Aware Adaptive Self-Consistency for Efficient Sampling in LLM Reasoning

arXiv:2601.02970v2 Announce Type: replace Abstract: Self-Consistency improves reasoning reliability through multi-sample aggregation, but incurs substantial inference cost. Adaptive self-consistency m

RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observation

arXiv:2604.17243v1 Announce Type: new Abstract: A robust Multimodal Large Language Model (MLLM) for Earth Observation should maintain consistent interpretation and reasoning under realistic input vari

safetyarxiv-cs-cv

Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning

arXiv:2601.14750v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting has achieved remarkable success in unlocking the reasoning capabilities of Large Language Models (LLMs). Although C

Tools

Replit for Startups is live. Up to $25K in credits to build your product, ship fast, and scale. If you're building on Replit, this is for yo…

Replit has launched a startup program offering up to $25,000 in credits to help founders build, launch, and scale their products on the Replit platform. The program is designed for startups actively u

toolsreplit--x

Industry

Report: Meta will train AI agents by tracking employees' mouse, keyboard use

Meta is installing tracking software on U.S.-based employees' computers to capture mouse movements, clicks, and keystrokes for training AI models to build autonomous AI agents . The tool focuses on ar

industryars-technica

Representation Before Training: A Fixed-Budget Benchmark for Generative Medical Event Models

model-releasesarxiv-cs-lg

arXiv:2604.16775v1 Announce Type: new Abstract: Every prediction from a generative medical event model is bounded by how clinical events are tokenized, yet input representation is rarely isolated from

Representation-Guided Parameter-Efficient LLM Unlearning

arXiv:2604.17396v1 Announce Type: new Abstract: Large Language Models (LLMs) often memorize sensitive or harmful information, necessitating effective machine unlearning techniques. While existing para

RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

arXiv:2604.17725v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong promise for mining Electronic Health Records (EHRs) by reasoning over longitudinal clinical information t

tutorialsarxiv-cs-cl

ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition

arXiv:2503.21248v3 Announce Type: replace Abstract: Large language models (LLMs) have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses r

Residual Diffusion Bridge Model for Image Restoration

arXiv:2510.23116v3 Announce Type: replace Abstract: Diffusion bridge models establish probabilistic paths between arbitrary paired distributions and exhibit great potential for universal image restora

Rethinking Cross-Dose PET Denoising: Mitigating Averaging Effects via Residual Noise Learning

arXiv:2604.16925v1 Announce Type: new Abstract: Cross-dose denoising for low-dose positron emission tomography (LDPET) has been proposed to address the limited generalization of models trained at a si

tutorialsarxiv-cs-cv

Rethinking Cross-Modal Fine-Tuning: Optimizing the Interaction Between Feature Alignment and Target Fitting

model-releasesarxiv-cs-lg

arXiv:2601.18231v4 Announce Type: replace Abstract: Adapting pre-trained models to unseen feature modalities has become increasingly important due to the growing need for cross-disciplinary knowledge

Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive Scoring

arXiv:2512.12069v3 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) are vulnerable to a growing array of multimodal jailbreak attacks, necessitating defenses that are both g

Rethinking Meeting Effectiveness: A Benchmark and Framework for Temporal Fine-grained Automatic Meeting Effectiveness Evaluation

arXiv:2604.17260v1 Announce Type: new Abstract: Evaluating meeting effectiveness is crucial for improving organizational productivity. Current approaches rely on post-hoc surveys that yield a single c

Rethinking Post-Unlearning Behavior of Large Vision-Language Models

arXiv:2506.02541v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) can recognize individuals in images and disclose sensitive personal information about them, raising criti

Rethinking the Comparison Unit in Sequence-Level Reinforcement Learning: An Equal-Length Paired Training Framework from Loss Correction to Sample Construction

arXiv:2604.17328v1 Announce Type: new Abstract: This paper investigates the length problem in sequence-level relative reinforcement learning. We observe that, although existing methods partially allev

safetyarxiv-cs-lg

Applications

Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure

arXiv:2412.15176v3 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly employed in real-world applications, driving the need to evaluate the trustworthiness of their generat

applicationsarxiv-cs-lg

ReTraceQA: Evaluating Reasoning Traces of Small Language Models in Commonsense Question Answering

arXiv:2510.09351v2 Announce Type: replace Abstract: While Small Language Models (SLMs) have demonstrated promising performance on an increasingly wide array of commonsense reasoning benchmarks, curren

ReTrack: Evidence-Driven Dual-Stream Directional Anchor Calibration Network for Composed Video Retrieval

model-releasesarxiv-cs-cv

arXiv:2604.17898v1 Announce Type: new Abstract: With the rapid growth of video data, Composed Video Retrieval (CVR) has emerged as a novel paradigm in video retrieval and is receiving increasing atten

Retrieval-Augmented Multimodal Model for Fake News Detection

arXiv:2604.18112v1 Announce Type: new Abstract: In recent years, multimodal multidomain fake news detection has garnered increasing attention. Nevertheless, this direction presents two significant cha

Reverse Constitutional AI: A Framework for Controllable Toxic Data Generation via Probability-Clamped RLAIF

arXiv:2604.17769v1 Announce Type: new Abstract: Ensuring the safety of large language models (LLMs) requires robust red teaming, yet the systematic synthesis of high-quality toxic data remains under-e

Revisiting a Pain in the Neck: A Semantic Reasoning Benchmark for Language Models

arXiv:2604.16593v1 Announce Type: new Abstract: We present SemanticQA, an evaluation suite designed to assess language models (LMs) in semantic phrase processing tasks. The benchmark consolidates exis

Revisiting Active Sequential Prediction-Powered Mean Estimation

model-releasesarxiv-cs-lg

arXiv:2604.18569v1 Announce Type: cross Abstract: In this work, we revisit the problem of active sequential prediction-powered mean estimation, where at each round one must decide the query probabilit