Search: “reasoning”

ChatSOP: An SOP-Guided MCTS Planning Framework for Controllable LLM Dialogue Agents

arXiv:2407.03884v4 Announce Type: replace-cross Abstract: Dialogue agents powered by Large Language Models (LLMs) show superior performance in various tasks. Despite the better user understanding and

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

CLAW: Learning Continuous Latent Action World Models via Adversarial Latent Regularization

DGX agent

arXiv:2606.04130v1 Announce Type: new Abstract: We introduce CLAW, a fully end-to-end self-supervised framework for learning a world model jointly with continuous latent action representations directl

researcharxiv-cs-ro

4 Jun 2026

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts

arXiv:2606.04661v1 Announce Type: new Abstract: Prompts tuned for accuracy often grow long, raising inference cost on every model call. The best accuracy-cost trade-off depends on the task and the bud

researcharxiv-cs-cl

DLLG: Dynamic Logit-Level Gating of LLM Experts

model-releasesarxiv-cs-cl

arXiv:2606.04378v1 Announce Type: new Abstract: Leveraging multiple specialized LLMs can combine complementary strengths, but existing approaches trade adaptability for stability: routing commits prem

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

arXiv:2606.04115v1 Announce Type: cross Abstract: Quantizing large language models (LLMs) to low-precision floating-point representations is central to efficient deployment, yet applying a single bit-

Applications

Fine-grained Fragment Retrieval in Multi-modal Long-form Dialogues

arXiv:2606.04591v1 Announce Type: new Abstract: With the widespread adoption of multi-modal communication platforms, long-form dialogues interleaving text and images have become increasingly common. U

applicationsarxiv-cs-cl

Graph Set Transformer

model-releasesarxiv-cs-lg

arXiv:2606.05116v1 Announce Type: new Abstract: We introduce the Graph Set Transformer (GST), a neural network architecture for learning on sets of graphs, designed for tasks in which per-element pred

GroupToM-Bench: Benchmarking Group Theory of Mind and Nonlinear Social Emergence in MLLMs

model-releasesarxiv-cs-cv

arXiv:2606.04184v1 Announce Type: new Abstract: True general intelligence requires not only a model of the physical world but also a social world model: the capacity to infer how individual mental sta

here’s why i think the situation may be dire: https://x.com/GaryMarcus/status/2062369417372258652?s=20

here’s why i think the situation may be dire: https://x.com/GaryMarcus/status/2062369417372258652?s=20 ⚠️Why didn’t the hyperscalers wait until after the IPO in switching to pay-by-usage-charging? My

agentsgary-marcus--x

Interfaze: The Future of AI is built on Task-Specific Small Models

arXiv:2602.04101v2 Announce Type: replace Abstract: We present Interfaze, a native hybrid model that fuses task-specific deep neural networks (CNNs and DNNs) directly into a transformer decoder throug

Tutorials

J-RAS: Mutual Adaptation for Medical Image Segmentation via Contrastive Retrieval-Augmented Joint Optimization

arXiv:2510.09953v3 Announce Type: replace Abstract: Manual medical image segmentation by clinicians, though accurate, is time-consuming and variable across experts, whereas AI-based models automate th

tutorialsarxiv-cs-cv

Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models

arXiv:2606.04672v1 Announce Type: cross Abstract: Continuous-time dynamic graphs (CTDGs) provide a richer framework to capture fine-grained temporal patterns in evolving relational data. Long-range in

Learning While Acting: A Skill-Enhanced Test-Time Co-Evolution Framework for Online Lifelong Learning Agents

arXiv:2606.04815v1 Announce Type: cross Abstract: Lifelong learning is essential for Large Language Model (LLM) agents operating in dynamic, interactive environments. However, existing lifelong learni

safetyarxiv-cs-ai

Listening to the Workforce: Measuring Construction Worker Safety Attitudes from Social Media Discourse Using LLMs

arXiv:2606.04450v1 Announce Type: new Abstract: Worker safety attitudes are key determinants of whether protective practices are applied or bypassed on construction sites. Yet measuring them at scale

safetyarxiv-cs-cl

Hardware

LLM Compression with Jointly Optimizing Architectural and Quantization choices

arXiv:2606.04063v1 Announce Type: cross Abstract: Deploying large language models (LLMs) is challenging due to their significant memory and computational requirements. While some methods address this

hardwarearxiv-cs-ai

M^3Eval: Multi-Modal Memory Evaluation through Cognitively-Grounded Video Tasks

arXiv:2606.05008v1 Announce Type: cross Abstract: As multi-modal models advance towards long-form video understanding, memory emerges as a critical capability. Despite substantial efforts in developin

MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation

arXiv:2606.04513v1 Announce Type: new Abstract: Lane-level maps are critical infrastructure for autonomous driving and lane-level navigation, yet constructing and maintaining standardized lane network

Med-Banana: Learning Quality-Controlled Medical Image Editing from Success-and-Failure Trajectories

arXiv:2511.00801v4 Announce Type: replace Abstract: Text-guided medical image editing must satisfy the requested pathology while preserving anatomy, modality-specific appearance, and clinical plausibi

researcharxiv-cs-cv

MENTOR: A Metacognition-Driven Self-Evolution Framework for Uncovering and Mitigating Implicit Domain Risks in LLMs

arXiv:2511.07107v3 Announce Type: replace Abstract: Ensuring the safety of Large Language Models (LLMs) is critical for real-world deployment. However, current safety measures often fail to address im

safetyarxiv-cs-ai

NVIDIA Nemotron 3 Ultra now available on Amazon SageMaker JumpStart

model-releasesaws-ml-blog

The search results primarily discuss the Nemotron 3 Nano Omni model rather than Nemotron 3 Ultra. However, I found a recent NVIDIA blog post reference that indicates Nemotron 3 Ultra is available thro

ollama run gemma4:12b Gemma 4 12B is updated on Ollama, and available across all platforms! Try it on: Claude Code ollama launch claude --mo…

ollama run gemma4:12b Gemma 4 12B is updated on Ollama, and available across all platforms! Try it on: Claude Code ollama launch claude --model gemma4:12b Hermes Agent ollama launch hermes --model gem

model-releasesollama--x

Parameter-Efficient Fine-Tuning with Learnable Rank

model-releasesarxiv-cs-cl

arXiv:2606.04325v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is a popular parameter-efficient fine-tuning (PEFT) method that restricts weight updates to low-rank adapters, introducing a

PoliticsBench: Benchmarking Political Values in Large Language Models with Multi-Turn Roleplay

arXiv:2603.23841v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) are increasingly used as primary sources of information, their potential for political bias may impact thei

Probing Outcome-Level Resemblance and Mechanism-Level Alignment in LLM Risk Decisions: Evidence from the St. Petersburg Game

arXiv:2606.04978v1 Announce Type: new Abstract: LLMs can appear cautious in risk decision-making tasks, yet cautious-looking outputs do not necessarily indicate alignment with human decision-making me

safetyarxiv-cs-cl

ps no fair just mimicing walkthroughs.

This post likely discusses concerns about AI systems that merely imitate or reproduce existing walkthroughs and instructional content rather than demonstrating genuine understanding or original proble

safetygary-marcus--x

Revisiting Vul-RAG: Reproducibility and Replicability of RAG-based Vulnerability Detection with Open-Weight Models

arXiv:2606.04739v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generatio

RL Excursions during Pre-Training: Re-examining Policy Optimization for LLM training

arXiv:2606.04272v1 Announce Type: new Abstract: The standard LLM training pipeline applies reinforcement learning (RL) only after pre-training and supervised fine-tuning (SFT). We question this status

safetyarxiv-cs-lg

Robust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language Models

arXiv:2502.01576v2 Announce Type: replace Abstract: Multi-modal Large Language Models (MLLMs) excel in vision-language tasks but remain vulnerable to visual adversarial perturbations that can induce h

safetyarxiv-cs-cv

SaliMory: Orchestrating Cognitive Memory for Conversational Agents

arXiv:2606.04120v1 Announce Type: cross Abstract: Conversational agents that serve as lifelong companions must maintain persistent memory across all interactions. However, simply expanding context win

Self-Reflective APIs: Structure Beats Verbosity for AI Agent Recovery

arXiv:2606.05037v1 Announce Type: cross Abstract: When an AI agent calls an API and hits a validation error, it needs more than what went wrong -- it needs what to do next. A self-reflective API retur

Local Ai

SemBlock: Semantic Boundary Dynamic Blocks for Diffusion LLMs

arXiv:2606.04964v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text through iterative denoising, and blockwise decoding improves their practicality by committing tokens in l

local-aiarxiv-cs-cl

SePO: Self-Evolving Prompt Agent for System Prompt Optimization

arXiv:2606.04465v1 Announce Type: cross Abstract: System prompt optimization improves agent behavior without modifying the underlying model, yielding human-readable, model-agnostic instructions. Exist

ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modeling

arXiv:2603.02697v2 Announce Type: replace-cross Abstract: This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works

SMAC-Talk: A Natural Language Extension of the StarCraft Multi-Agent Challenge for Large Language Models

arXiv:2606.04202v1 Announce Type: new Abstract: As LLMs become more widely deployed, they are increasingly expected to work alongside other AI agents rather than operating in isolation. Effective coor

SMADE-IE: Sparse Multi-Agent Framework with Evidence-Driven Debate for Zero-Shot Information Extraction

model-releasesarxiv-cs-cl

arXiv:2606.04691v1 Announce Type: new Abstract: Zero-shot information extraction (IE) with large language models (LLMs) has attracted increasing attention due to its flexibility in adapting to new sch

Supportive Token Revealing for Fast Diffusion Language Model Decoding

arXiv:2606.04236v1 Announce Type: cross Abstract: Discrete diffusion language models can generate text efficiently by updating multiple masked positions in parallel, but this parallelism introduces a

Test-Time Compute Scaling for ASR with Depth-Conditioned Looped Transformers

model-releasesarxiv-cs-lg

arXiv:2606.04678v1 Announce Type: new Abstract: End-to-end ASR systems typically use fixed-depth acoustic encoders at inference, making it difficult to trade additional test-time computation for impro

The Saturation Trap and the Subjectivity of Intervention Timing: Why Affect-Based Triggers and LLM Judges Fail to Time Interventions on Autonomous Agents

arXiv:2606.04296v1 Announce Type: new Abstract: As autonomous AI agents move from conversational systems to long-horizon software execution, runtime safety layers that decide when to interrupt an agen

Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research

arXiv:2606.04152v1 Announce Type: new Abstract: Large language models are reshaping research practice while quietly eroding researchers epistemic accountability. This commentary introduces PEEL - Prot

transitions like this are why we think it's helpful to have a provider-agnostic harness we used to talk more about swapping models when the …

model-releasesharrison-chase--x

transitions like this are why we think it's helpful to have a provider-agnostic harness we used to talk more about swapping models when the latest and greatest came out -- but the latest and greatest

T^star: Progressive Block Scaling for Masked Diffusion Language Models Through Trajectory Aware Reinforcement Learning

arXiv:2601.11214v5 Announce Type: replace Abstract: We present T^star, a simple TraceRL-based training curriculum for progressive block-size scaling in masked diffusion language models (MDMs). Startin

researcharxiv-cs-cl

WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation

arXiv:2606.04907v1 Announce Type: new Abstract: Visual navigation requires generating smooth and collision-free trajectories under complex geometric and physical constraints. Existing reactive policie

safetyarxiv-cs-ro

We're presenting ParseBench at CVPR 2026! ParseBench is the most comprehensive document understanding benchmark for VLMs. ✅ It contains 2k p…

model-releasesjerry-liu--x

We're presenting ParseBench at CVPR 2026! ParseBench is the most comprehensive document understanding benchmark for VLMs. ✅ It contains 2k pages of real-world enterprise documents ✅ It has comprehensi

When Clients Stop Following: A Cognitive Conceptualization Diagram-driven Framework for Strategic Counseling

arXiv:2606.04389v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise in psychological counseling, yet existing benchmarks rely heavily on highly cooperative simulated clients. We

researcharxiv-cs-cl

A 3D Isovist World Model -- Revealing a City's Unseen Geometry and Its Emergent Cross-City Signature

model-releasesarxiv-cs-lg

arXiv:2606.03609v1 Announce Type: cross Abstract: Embodied agents that navigate cities rely on world models that predict how their surroundings will change as they move. But for navigation, what matte

3 Jun 2026

Tutorials

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners

arXiv:2606.03685v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) improves end-to-end classical planning in large language models (LLMs), but do these models also learn to represent and r

tutorialsarxiv-cs-ai

3 Jun 2026

Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate

arXiv:2606.02670v1 Announce Type: cross Abstract: Many recent multivariate time series anomaly detection (MT-SAD) models incorporate cross-channel modeling, under the implicit assumption that the stru