Search: “reasoning”

Entropy Centroids as Intrinsic Rewards for Test-Time Scaling

arXiv:2604.26173v1 Announce Type: cross Abstract: An effective way to scale up test-time compute of large language models is to sample multiple responses and then select the best one, as in Grok Heavy

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Evaluation Revisited: A Taxonomy of Evaluation Concerns in Natural Language Processing

DGX agent

arXiv:2604.25923v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have prompted a growing body of work that questions the methodology of prevailing evaluation practices.

researcharxiv-cs-cl

30 Apr 2026

Glance-or-Gaze: Incentivizing LMMs to Adaptively Focus Search via Reinforcement Learning

arXiv:2601.13942v2 Announce Type: replace-cross Abstract: Large Multimodal Models (LMMs) have achieved remarkable success in visual understanding, yet they struggle with knowledge-intensive queries in

safetyarxiv-cs-ai

Graph-based Semantic Calibration Network for Unaligned UAV RGBT Image Semantic Segmentation and A Large-scale Benchmark

model-releasesarxiv-cs-cv

arXiv:2604.26893v1 Announce Type: new Abstract: Fine-grained RGBT image semantic segmentation is crucial for all-weather unmanned aerial vehicle (UAV) scene understanding. However, UAV RGBT semantic s

Hermes Agent + LM Studio 👾🪽

Hermes Agent + LM Studio 👾🪽 LM Studio is the most popular way to run open-source LLMs on your own hardware. Your Hermes Agent now runs natively on @lmstudio: auto-discovering your models, loading them

agentsnous-research--x

Heterogeneous Adaptive Policy Optimization: Tailoring Optimization to Every Token's Nature

arXiv:2509.16591v2 Announce Type: replace Abstract: Using entropy as a measure of heterogeneity to guide optimization has emerged as a crucial research direction in Reinforcement Learning for LLMs. Ho

Applications

Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models

arXiv:2401.00761v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) like ChatGPT are foundational in various applications due to their extensive knowledge from pre-training and fine

applicationsarxiv-cs-ai

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation

arXiv:2511.20714v2 Announce Type: replace-cross Abstract: World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic

LATTICE: Evaluating Decision Support Utility of Crypto Agents

arXiv:2604.26235v1 Announce Type: cross Abstract: We introduce LATTICE, a benchmark for evaluating the decision support utility of crypto agents in realistic user-facing scenarios. Prior crypto agent

LM Studio is the most popular way to run open-source LLMs on your own hardware. Your Hermes Agent now runs natively on @lmstudio: auto-disco…

LM Studio is the most popular way to run open-source LLMs on your own hardware. Your Hermes Agent now runs natively on @lmstudio: auto-discovering your models, loading them on demand with the right co

agentsnous-research--x

Operating-Layer Controls for Onchain Language-Model Agents Under Real Capital

arXiv:2604.26091v1 Announce Type: new Abstract: We study reliability in autonomous language-model agents that translate user mandates into validated tool actions under real capital. The setting is DX

safetyarxiv-cs-ai

OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction

arXiv:2604.25602v2 Announce Type: replace Abstract: Deploying production-ready multi-agent systems (MAS) in complex industrial environments remains challenging due to limitations in scalability, obser

agentsarxiv-cs-ai

Preserving Disagreement: Architectural Heterogeneity and Coherence Validation in Multi-Agent Policy Simulation

arXiv:2604.26561v1 Announce Type: cross Abstract: Multi-agent deliberation systems using large language models (LLMs) are increasingly proposed for policy simulation, yet they suffer from artificial c

ReLoop: Structured Modeling and Behavioral Verification for Reliable LLM-Based Optimization

arXiv:2602.15983v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can translate natural language into optimization code, but silent failures pose a critical risk: code that execut

SAGE: A Strategy-Aware Graph-Enhanced Generation Framework For Online Counseling

arXiv:2604.26630v1 Announce Type: new Abstract: Effective mental health counseling is a complex, theory-driven process requiring the simultaneous integration of psychological frameworks, real-time dis

Stress Testing Factual Consistency Metrics for Long-Document Summarization

arXiv:2511.07689v2 Announce Type: replace-cross Abstract: Evaluating the factual consistency of abstractive text summarization remains a significant challenge, particularly for long documents, where c

SWE-Edit: Rethinking Code Editing for Efficient SWE-Agent

arXiv:2604.26102v1 Announce Type: cross Abstract: Large language model agents have achieved remarkable progress on software engineering tasks, yet current approaches suffer from a fundamental context

The Dual Role of Abstracting over the Irrelevant in Symbolic Explanations: Cognitive Effort vs. Understanding

arXiv:2602.03467v2 Announce Type: replace Abstract: Explanations are central to human cognition, yet AI systems often produce outputs that are difficult to understand. While symbolic AI offers a trans

researcharxiv-cs-ai

The Serial Scaling Hypothesis

arXiv:2507.12549v4 Announce Type: replace Abstract: While machine learning has advanced through massive parallelization, we identify a critical blind spot: some problems are fundamentally sequential.

researcharxiv-cs-lg

The Zig project's rationale for their firm anti-AI contribution policy

Zig has one of the most stringent anti-LLM policies of any major open source project: No LLMs for issues. No LLMs for pull requests. No LLMs for comments on the bug tracker, including translation. Eng

safetysimon-willison

Through a Compressed Lens: Investigating The Impact of Quantization on Factual Knowledge Recall

arXiv:2505.13963v3 Announce Type: replace Abstract: Quantization methods are widely used to accelerate inference and streamline the deployment of large language models (LLMs). Although quantization's

Time Blindness: Why Video-Language Models Can't See What Humans Can?

arXiv:2505.24867v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have made impressive strides in understanding spatio-temporal relationships in videos. Howeve

Training-Free Adaptation of New-Generation LLMs using Legacy Clinical Models

arXiv:2601.03423v3 Announce Type: replace-cross Abstract: Adapting language models to the clinical domain through continued pretraining and instruction tuning requires costly retraining for each new m

Applications

Uncertainty-Aware Pedestrian Attribute Recognition via Evidential Deep Learning

arXiv:2604.26873v1 Announce Type: new Abstract: We propose UAPAR, an Uncertainty-Aware Pedestrian Attribute Recognition framework. To the best of our knowledge, this is the first EDL-based uncertainty

applicationsarxiv-cs-cv

Value-Guided Iterative Refinement and the DIQ-H Benchmark for Evaluating VLM Robustness

arXiv:2512.03992v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are essential for embodied AI and safety-critical applications, such as robotics and autonomous systems. However

Verified Critical Step Optimization for LLM Agents

arXiv:2602.03412v2 Announce Type: replace Abstract: As large language model agents tackle increasingly complex long-horizon tasks, effective post-training becomes critical. Prior work faces fundamenta

ViTaPEs: Visuotactile Position Encodings for Cross-Modal Alignment in Multimodal Transformers

arXiv:2505.20032v3 Announce Type: replace Abstract: Tactile sensing provides local essential information that is complementary to visual perception, such as texture, compliance, and force. Despite rec

safetyarxiv-cs-cv

Tutorials

Warning: GenAI-induced cognitive surrender may kill innovation. Consider the following, from CEO @wadhwa’s newsletter: “I have been speaking…

Warning: GenAI-induced cognitive surrender may kill innovation. Consider the following, from CEO @wadhwa’s newsletter: “I have been speaking with recent graduates in India, many of them highly recomme

tutorialsgary-marcus--x

$3/million output tokens. Qwen 3.5 Plus is basically a frontier model. Let that sink in.

model-releasestogether-ai--x

$3/million output tokens. Qwen 3.5 Plus is basically a frontier model. Let that sink in. Introducing Qwen3.6-Plus from @Alibaba_Qwen, a 1M-context model built for real-world agents, agentic coding, an

Align then Adapt: Rethinking Parameter-Efficient Transfer Learning in 4D Perception

model-releasesarxiv-cs-cv

arXiv:2602.23069v2 Announce Type: replace Abstract: Point cloud video understanding is critical for robotics as it accurately encodes motion and scene interaction. We recognize that 4D datasets are fa

Am I the only one that still likes ChatGPT? And I use Claude also

A Reddit discussion from r/ChatGPT in which a user expresses their continued preference for ChatGPT while also using Claude, likely exploring whether other users share similar sentiments about ChatGPT

model-releasesr-chatgpt

ANCHOR: A Physically Grounded Closed-Loop Framework for Robust Home-Service Mobile Manipulation

arXiv:2604.25323v1 Announce Type: new Abstract: Recent advances in open-vocabulary mobile manipulation have brought robots into real domestic environments. In such settings, reliable long-horizon exec

safetyarxiv-cs-ro

BARRED: Synthetic Training of Custom Policy Guardrails via Asymmetric Debate

arXiv:2604.25203v1 Announce Type: new Abstract: Deploying guardrails for custom policies remains challenging, as generic safety models fail to capture task-specific requirements, while prompting LLMs

Benchmarking Logistic Regression, SVM, and LightGBM Against BiLSTM with Attention for Sentiment Analysis on Indonesian Product Reviews

arXiv:2604.25452v1 Announce Type: new Abstract: Sentiment analysis of product reviews on e-commerce platforms plays a critical role in automatically understanding customer satisfaction and providing a

Benchmarking PyCaret AutoML Against IndoBERT Fine-Tuning for Sentiment Analysis on Indonesian IKN Twitter Data

arXiv:2604.25392v1 Announce Type: new Abstract: This paper benchmarks a classical machine learning approach based on PyCaret AutoML against a deep learning approach based on IndoBERT fine-tuning for b

CGU-ILALab at FoodBench-QA 2026: Comparing Traditional and LLM-based Approaches for Recipe Nutrient Estimation

arXiv:2604.25774v1 Announce Type: new Abstract: Accurate nutrient estimation from unstructured recipe text is an important yet challenging problem in dietary monitoring, due to ambiguous ingredient te

Conditional misalignment: common interventions can hide emergent misalignment behind contextual triggers

arXiv:2604.25891v1 Announce Type: new Abstract: Finetuning a language model can lead to emergent misalignment (EM) [Betley et al., 2025b]. Models trained on a narrow distribution of misaligned behavio

safetyarxiv-cs-lg

Cutscene Agent: An LLM Agent Framework for Automated 3D Cutscene Generation

arXiv:2604.25318v1 Announce Type: cross Abstract: Cutscenes are carefully choreographed cinematic sequences embedded in video games and interactive media, serving as the primary vehicle for narrative

DEGround: An Effective Baseline for Ego-centric 3D Visual Grounding with a Homogeneous Framework

arXiv:2506.05199v3 Announce Type: replace Abstract: A core task in embodied intelligence is ego-centric 3D visual grounding. Existing methods typically adopt two-stage, heterogeneous pipelines that pa

safetyarxiv-cs-cv

Do LLMs Capture Embodied Cognition and Cultural Variation? Cross-Linguistic Evidence from Demonstratives

arXiv:2604.25423v1 Announce Type: new Abstract: Do large language models (LLMs) truly acquire embodied cognition and cultural conventions from text? We introduce demonstratives, fundamental spatial ex

Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane

arXiv:2604.25885v1 Announce Type: cross Abstract: Graph neural networks such as ParticleNet and transformer based networks on point clouds such as ParticleTransformer achieve state-of-the-art performa

researcharxiv-cs-lg

FCMBench-Video: Benchmarking Document Video Intelligence

model-releasesarxiv-cs-cv

arXiv:2604.25186v1 Announce Type: new Abstract: Document understanding is a critical capability in financial credit review, onboarding, and remote verification, where both decision accuracy and eviden

From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling

arXiv:2604.25847v1 Announce Type: cross Abstract: Optimization modeling underpins real-world decision-making in logistics, manufacturing, energy, and public services, but reliably solving such problem

agentsarxiv-cs-lg

Local Ai

From World-Gen to Quest-Line: A Dependency-Driven Prompt Pipeline for Coherent RPG Generation

arXiv:2604.25482v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for narrative generation, but their use in complex, multi-layered role-playing game (RPG) world

local-aiarxiv-cs-cl

GeoSearch: Augmenting Worldwide Geolocalization with Web-Scale Reverse Image Search and Image Matching

arXiv:2604.25390v1 Announce Type: cross Abstract: Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity.

researcharxiv-cs-cv

I released LLM 0.32a0 this morning, a major backwards-compatible refactor of my LLM Python library and CLI tool for working with language mo…

model-releasessimon-willison--x

I released LLM 0.32a0 this morning, a major backwards-compatible refactor of my LLM Python library and CLI tool for working with language models - the new changes should help LLM work better with reas

Large Language Models Explore by Latent Distilling

arXiv:2604.24927v1 Announce Type: new Abstract: Generating diverse responses is crucial for test-time scaling of large language models (LLMs), yet standard stochastic sampling mostly yields surface-le

MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts

arXiv:2411.14721v2 Announce Type: replace Abstract: Molecule discovery is a pivotal research field, impacting everything from medicine to materials. Recently, Large Language Models (LLMs) have been wi