Search: “reasoning”

Reproducibility seems to be headed towards irrelevance in ML research. Is it too late? [D]

researchr-machinelearning

I feel that reproducibility is now a lost cause in machine learning research for three reasons: Many research is moving towards the physical AI territory, where you need expensive hardwares or even en

6 Sept 2026

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Model Releases

NInfer fork: 555k context@fp4 for 5090 with YARN, reliable kv host cacheing, monitoring, jinja, opened model support

DGX agent

Hiya, NInfer is amazng for Qwen, but lacking for real-world-use. As adoption of issues/pr's was not really what I needed, I created a fork and hit it for this week with 3 concurrent claude code sessio

model-releasesr-localllama

5 Sept 2026

NInfer vs llama.cpp vs vLLM: quality + speed comparison for Qwen3.8-27B NVFP4 on RTX 5090

model-releasesr-localllama

I've been running Qwen3.8-27B as a local inference server for a production content intelligence pipeline (HVAC industry stuff, lots of long-context retrieval and structured extraction). I have been wa

5 Sept 2026

A Circuit for Plural Reference: How LLMs Represent and Retrieve Singular and Plural Entities

arXiv:2609.03687v1 Announce Type: new Abstract: Coreference resolution is an important task in contextual reasoning. In this paper, we investigate the mechanism for representing and retrieving singula

researcharxiv-cs-cl

A Computationally Feasible Framework for Causal Probabilistic Explanation

arXiv:2609.04177v1 Announce Type: new Abstract: Explaining why a specific outcome occurred, and which inputs deserve the blame or credit, is central to philosophical, scientific, and policy analysis.

Industry

A group of incredibly talented and dedicated engineers made Cybercab happen. If you want to join them, we’re hiring AI engineers across the …

A group of incredibly talented and dedicated engineers made Cybercab happen. If you want to join them, we’re hiring AI engineers across the board: scaling, data, RL, reasoning, evals, world models, au

industryelon-musk--x

Astra is a genuine improvement but not even off trend. So much for GPT-6 being AGI, folks. (i think we can safely assume that real AGI would…

Astra is a genuine improvement but not even off trend. So much for GPT-6 being AGI, folks. (i think we can safely assume that real AGI would be significantly above the trend line,) GPT-6 Astra has set

safetygary-marcus--x

BASP: Communication-Efficient Batch-Aware Sequence Parallelism for LLM Training

model-releasesarxiv-cs-lg

arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due t

Beyond Shallow Alignment: How Post-Training Methods Determine Refusal Circuits And Steering Robustness

model-releasesarxiv-cs-cl

arXiv:2609.03887v1 Announce Type: new Abstract: How do the methods used to train language models to refuse harmful requests shape how that refusal actually works inside the model? We compare three pos

Check out this week’s shipping recap: — Gemini 3.8 Flash, our most intelligent workhorse model yet, delivers upgrades across coding, agentic…

model-releasesgoogle-ai--x

Check out this week’s shipping recap: — Gemini 3.8 Flash, our most intelligent workhorse model yet, delivers upgrades across coding, agentic workflows, and critical multi-step reasoning. — Gemini 3.8

Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2609.04070v1 Announce Type: new Abstract: Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a

InSituMeasure: Probing Situated Measurement Grounding in Industrial Scenes with Multimodal Large Language Models

arXiv:2609.04014v1 Announce Type: new Abstract: For trained operators, gauge reading requires little specialized knowledge, low cognitive effort, and high repeatability. Yet Multimodal Large Language

Judging LLM-as-a-Judge: Concerning Rubric Artifacts in LLM-based Automated Text Generation Evaluation

arXiv:2609.02942v1 Announce Type: cross Abstract: LLM-as-a-Judge pipelines are increasingly used to evaluate AI-generated text, based on the assumption that judgments arise from reasoning over candida

Large Language Models in Resolving Contextual Knowledge Conflicts

arXiv:2609.03148v1 Announce Type: new Abstract: Most prior works focused on conflicts between an LLM's internal parametric knowledge and externally provided context. In contrast, we investigate how LL

safetyarxiv-cs-cl

MemoryLACE: Memory Lifecycle-Aware Consolidation and Evidence Retrieval

arXiv:2609.03201v1 Announce Type: new Abstract: Long-term LLM agents must preserve information across interactions while distinguishing repeated evidence, historical states, updates, and unresolved co

researcharxiv-cs-cl

NeoRed: A Knowledge-Logic-Alignment Multimodal Large Language Model for Neonatal Respiratory Disease Diagnosis

arXiv:2609.03527v1 Announce Type: new Abstract: Neonatal respiratory diseases are a major cause of neonatal morbidity and mortality, posing substantial challenges in clinical practice. Despite recent

R^{2}Adapter: A Routing and Rewriting Adapter for Efficient Hybrid RAG

arXiv:2609.02894v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a prevailing paradigm for enhancing Large Language Models (LLMs) with non-parametric knowledge. Vanilla

researcharxiv-cs-cl

Sequential Beats Joint: On the Interplay between On-Policy Distillation and RLVR

arXiv:2609.04108v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) have emerged as two dominant methods for post-training reasonin

Tutorials

Sparse auto-regressive modeling for scene generation from multi-view images

arXiv:2609.03931v1 Announce Type: new Abstract: Generating complete 3D scenes from sparse, unconstrained views is a fundamental challenge in 3D vision which requires reasoning beyond observed content

tutorialsarxiv-cs-cv

Automated Maize Ear Phenotyping Using 3D Reconstructions

arXiv:2609.01921v1 Announce Type: new Abstract: Maize kernel traits such as row number, kernels per row, and kernel size vary largely for genetic reasons and are consistently associated with regions o

researcharxiv-cs-cv

Agents

Bilevel Coordinated Reflection: A Game-Theoretic Approach to Multi-Agent LLM Systems

arXiv:2609.02750v1 Announce Type: new Abstract: Multi-agent LLM systems commonly use an orchestrator to decompose a task for a team of workers and then improve through textual reflection. Despite stro

agentsarxiv-cs-ai

CLASE: A Hybrid Method for Chinese Legalese Stylistic Evaluation

arXiv:2602.12639v2 Announce Type: replace Abstract: Legal text generated by large language models (LLMs) can usually achieve reasonable factual accuracy, but it frequently fails to adhere to the speci

safetyarxiv-cs-cl

Agents

CrowdStrike’s Falcon Guardian shrinks an AI agent’s blast radius

An AI agent doesn’t need to be malicious to cause damage. It just needs to reason its way into the wrong system, the way a well-meaning agent handling a finance report might decide it needs a code rep

agentssiliconangle

Does Playing it Safe Count as Faithfulness? Reassessing LVLM Hallucination Mitigation Methods

model-releasesarxiv-cs-cv

arXiv:2609.01888v1 Announce Type: new Abstract: Recent inference-time hallucination mitigation methods for large vision-language models (LVLMs) report strong gains on hallucination benchmarks. However

Evidence-Guided Detection, Localization and Explanation for Text-Centric Image Forensics

arXiv:2609.02097v1 Announce Type: new Abstract: The rapid progress of AIGC has made text-centric image manipulation increasingly accessible, creating new forensic challenges that require not only auth

local-aiarxiv-cs-cv

GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2312.06315v2 Announce Type: replace Abstract: Warning: This paper contains content that may be offensive or upsetting. There has been a significant increase in the usage of large language models

HarmReduction: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs

model-releasesarxiv-cs-cl

arXiv:2507.21815v2 Announce Type: replace Abstract: Millions of individuals' well-being are challenged by the harms of substance use. Harm reduction as a public health strategy provides non-judgementa

Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool Primitives

arXiv:2609.01736v1 Announce Type: cross Abstract: Large language models (LLMs) augmented with external tools have demonstrated remarkable capability in solving complex real-world tasks. However, exist

Humanoid Safe Stop via Learned Stoppability Value

arXiv:2609.02358v1 Announce Type: cross Abstract: Humanoid robots responding to emergency stop commands typically execute a fixed maneuver, without reasoning about whether a safe stop is actually feas

safetyarxiv-cs-lg

Agents

Hybrid Retrieval-Augmented Generation with Knowledge Graph Expansion, RRF Fusion, and Per-Chunk Grounded Evaluation for Enterprise Document Search

arXiv:2609.01617v1 Announce Type: cross Abstract: Getting accurate, grounded answers out of large enterprise document repositories is a difficult problem. Dense vector retrieval alone frequently perfo

agentsarxiv-cs-ai

Improving Evaluation Realism with Inference-Time Compute and Deployment Scaffolds

arXiv:2609.02302v1 Announce Type: new Abstract: A core obstacle to alignment evaluation is evaluation awareness: capable models can tell when they are being tested rather than deployed, weakening the

Multimodal Language Models as Text-to-Image Model Evaluators

arXiv:2505.00759v3 Announce Type: replace-cross Abstract: The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on stat

NE-R1: Enhancing Named Entity Recognition Model via Reinforcement Learning

arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo

Zeta-Lite: A Concurrent, Branchable In-Browser SQL Database for Agentic Memory

arXiv:2609.01818v1 Announce Type: cross Abstract: The browser has become a first-class database host: applications increasingly want to store, query, and reason over structured data entirely on the cl

local-aiarxiv-cs-ai

🏆 #1 on CodeArena: WebDev leaderboard. Qwen3.8-Max-0902 jumps from 1669 to 1691, setting a new record for agentic coding (WebDev) workflows…

🏆 #1 on CodeArena: WebDev leaderboard. Qwen3.8-Max-0902 jumps from 1669 to 1691, setting a new record for agentic coding (WebDev) workflows, with standout strength in multistep reasoning, tool use, an

model-releasesqwen--x

Are We There Yet? Assessing Computer-Use Agents for Blind Users' Accessible Interaction with Desktop Applications

arXiv:2609.00524v1 Announce Type: cross Abstract: Computer-use agents are emerging as a paradigm for agentic human-AI interaction, combining language reasoning with multi-modal interface grounding to

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

local-aiarxiv-cs-ai

DSG: Dynamic 3D Scene Graph Construction for Embodied Agents in Changing Indoor Environments

model-releasesarxiv-cs-ro

arXiv:2609.00619v1 Announce Type: new Abstract: In indoor environments, object positions frequently change due to human activities or embodied-agent interactions, causing previously constructed scene

Dual Process Motion Planning

arXiv:2609.01260v1 Announce Type: new Abstract: Robotic systems are deeply embedded in both industry and everyday life, where they are expected to act with speed, precision, and reliability. Classical

DualStake: Dual-Path Confidence Calibration in Deep Research Agents

arXiv:2609.00935v1 Announce Type: cross Abstract: Deep Research agents tackle knowledge-intensive tasks through multi-round retrieval and decision-oriented generation. However, these agents suffer fro

EvoSCM: Scientific Belief Revision Through Causal Model Evolution and Experimentation

arXiv:2609.01526v1 Announce Type: new Abstract: Scientific agents must learn not only how to reason, but also what to believe. However, existing LLM agents typically express scientific hypotheses in f

Applications

Feed-Forward Multi-view Multi-person Reconstruction with Contrastive Human-Aware 3D Representation

arXiv:2609.00745v1 Announce Type: new Abstract: Multi-view human reconstruction has been extensively studied under simplified settings, yet robust and efficient multi-person reconstruction in unconstr

applicationsarxiv-cs-cv

GRRM: Group Relative Reward Modeling for Machine Translation

arXiv:2602.14028v2 Announce Type: replace Abstract: While Group Relative Policy Optimization (GRPO) offers a powerful framework for LLM post-training, its effectiveness in open-ended domains like Mach

safetyarxiv-cs-cl

If this is true, OpenAI seems to be violating one of the few redlines that exist in the AI industry. Absolutely do not train your models lik…

If this is true, OpenAI seems to be violating one of the few redlines that exist in the AI industry. Absolutely do not train your models like this - what is going on?? Really huge and extremely concer

safetygary-marcus--x

Make Some Noise: Unsupervised Remote Sensing Change Detection Using Latent Space Perturbations

arXiv:2602.19881v2 Announce Type: replace-cross Abstract: Unsupervised remote sensing change detection (UCD) aims to localise changes between two images of the same region without relying on labelled

local-aiarxiv-cs-ai

MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery

arXiv:2603.03517v2 Announce Type: replace-cross Abstract: General-purpose large language models (LLMs) that rely on in-context learning do not reliably deliver the scientific understanding and perform

Probing Factual Knowledge Transfer with Training Data Interventions

arXiv:2609.01341v1 Announce Type: cross Abstract: Do multilingual language models transfer factual knowledge across languages during continued pretraining, or do they mostly recall facts learned direc

Qwen will be the king?

model-releasesr-localllama

Extended reasoning and post-training appear to be the keys used by DeepSeek, Qwen, and GLM to boost performance (leveraging higher token counts). And Qwen 4 hasn't even been released yet. Of course, w