Search: “reasoning”

ASPIRE: Asynchronous Batched Self-Speculative Decoding for Long-Context LLM Inference

arXiv:2609.17943v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by attention, whose repeated KV-cache reads make decoding memory-bound. Self-speculative decoding alleviate

researcharxiv-cs-cl

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

BadQubits: An LLM-Based Framework for Static Pre-Execution Detection of Structurally Harmful Quantum Circuits

DGX agent

arXiv:2609.18965v1 Announce Type: cross Abstract: This paper presents BadQubits, an LLM-based framework for static pre-execution detection of structurally harmful OpenQASM 2.0 circuits. The framework

model-releasesarxiv-cs-ai

17 Sept 2026

Beyond Truncation: Rethinking LLM Decoding as Ensemble Pruning

arXiv:2609.18723v1 Announce Type: new Abstract: We introduce Mahalanobis-Ensemble Decoding (ME-Decoding), a novel Large Language Model (LLM) decoding framework that frames candidate token selection as

researcharxiv-cs-ai

Bias Amplification in Multi-Agent Network: How Biased Agents Shape Opinions and Rhetoric

model-releasesarxiv-cs-lg

arXiv:2609.18306v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in applications involving interaction between agents, where their output plays a role in collecti

CaSCo: Cascade-Aware Soft-Collision Motion Planning

arXiv:2609.18910v1 Announce Type: new Abstract: Conventional motion planning treats collision as a binary constraint, although contact with different objects can have drastically different consequence

researcharxiv-cs-ro

Decodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition

arXiv:2609.18080v1 Announce Type: new Abstract: Linear probes can decode safety-relevant concepts such as truthfulness from language-model activations, but probe accuracy may show only decodability, n

safetyarxiv-cs-ai

Do Frontier Models Seek Safety Evidence Before Acting?

arXiv:2609.17865v1 Announce Type: new Abstract: Frontier models are often evaluated on how they respond to safety information once it is already in context. We study an earlier decision point: whether

Do Social Patterns Hold in Synthetic Data? Analyzing Cyberbullying Dynamics in LLM-Generated and Authentic Dialogues

arXiv:2609.17549v1 Announce Type: new Abstract: Cyberbullying (CB) is a complex social phenomenon characterized by repeated aggression, power imbalance, and multi-party interaction. Although large lan

DualSQL: Text-to-SQL with Multi-Agent Reinforcement Learning

arXiv:2609.18135v1 Announce Type: cross Abstract: State-of-the-art Text-to-SQL systems are typically multi-agent pipelines centered around two fundamental tasks: schema linking and SQL generation. How

safetyarxiv-cs-ai

Echo: Learning-based Matching Decompilation using Trusted Back Translation

arXiv:2609.18706v1 Announce Type: cross Abstract: Neural decompilers can recover readable and recompilable source code from binaries, but their predictions remain difficult to trust. Matching decompil

EmboAlign: Aligning Video Generation with Compositional Constraints for Zero-Shot Manipulation

arXiv:2603.05757v2 Announce Type: replace Abstract: Video generative models (VGMs) pretrained on large-scale internet data can produce temporally coherent rollout videos that capture rich object dynam

safetyarxiv-cs-ro

English Word Sense Disambiguation in 2026: When the Labels Become the Bottleneck

arXiv:2609.17554v1 Announce Type: new Abstract: In English all-words word sense disambiguation (WSD), the labels, not the models, have become the bottleneck: frontier LLMs are accurate enough that the

Local Ai

Entropy in Conversational AI: Structured Unpredictability as Inferrable Interiority

arXiv:2609.19044v1 Announce Type: new Abstract: Sampling can increase response diversity without producing history-dependent behavior. We formalize a different design target, structured unpredictabili

local-aiarxiv-cs-cl

Evidence-Grounded Agentic Formulation Development in an Autonomous Laboratory

model-releasesarxiv-cs-lg

arXiv:2609.19099v1 Announce Type: new Abstract: Self-emulsifying drug delivery systems (SEDDS) can improve the oral bioavailability of poorly soluble drugs, but identifying high-performing formulation

Agents

Faithful yet Collusive: Why Chain-of-Thought Monitoring Cannot Detect Collusion in LLM Pricing Agents under Oligopolistic Competition

arXiv:2609.18346v1 Announce Type: new Abstract: Large language models (LLM) deployed as autonomous pricing agents may sustain supracompetitive prices through tacit coordination. We develop a causal gr

agentsarxiv-cs-ai

Hardware

Fathom: Per-Query Read Depth for Sparse Decoding over Offloaded KV Caches

arXiv:2609.17652v1 Announce Type: cross Abstract: When agentic sessions run to a million tokens with many sessions resident at once, the KV cache and the index that ranks it live in host memory, and t

hardwarearxiv-cs-cl

Future of general LLM work (interp/inference/alignment) vs agentic/physical AI (VLA, multimodal) for career [D]

I'm at a crossroads with two grad school options that would take me in somewhat different research directions, and I wanted some general advice on these fields, their growth, and industry alignment. I

safetyr-machinelearning

@GaryMarcus @0xkkai The current AI agency architecture based on looping on an LLM core by piling on the same LLM context is a deeply flawed …

Romeo Lupascu has criticized the prevailing AI agency framework, which relies on repeatedly looping an LLM core with identical context. He calls this strategy “deeply flawed” and argues that it should

safetygary-marcus--x

“HUMANZS LAUNCHED THE JOB” Ok, I don’t like the spelling here, but the gist of this Mozilla cybersecurity researcher rings true. The six new…

“HUMANZS LAUNCHED THE JOB” Ok, I don’t like the spelling here, but the gist of this Mozilla cybersecurity researcher rings true. The six new incidents aren’t about the second coming of Skynet, they ar

safetygary-marcus--x

Local Ai

Humor Arena: Which LLM is the funniest?

We compared 20 model versions on 360 frozen joke prompts, with four jokes requested per prompt and model names hidden from our humor-trained judge. Fable 5 had the highest estimated score: 66.8 points

local-air-localllama

Local Ai

I literally built the Jev architecture one year back and completely open-sourced it with model, dataset and paper

Everyone now talks about the architecture that's not auto regressive and does lightning fast probability prediction with a json schema. I worked on this literally one year back in March 2025, publishe

local-air-localllama

LM Fight Arena: Benchmarking Large Multimodal Models via Game Competition

arXiv:2510.08928v2 Announce Type: replace Abstract: Existing benchmarks for large multimodal models (LMMs) often fail to capture their performance in real-time, adversarial environments. We introduce

Applications

Long-Context Demonstration Selection Using State Space Models

arXiv:2609.17888v1 Announce Type: cross Abstract: We study the problem of demonstration selection, which involves selecting a subset of examples for prepending to a query to a language model. This pro

applicationsarxiv-cs-cl

Made in Hungary: Comments on the performance of generative language models

arXiv:2609.18284v1 Announce Type: new Abstract: In recent years, three initiatives have emerged to develop generative language models in Hungary. The motivation behind them is the same. For Hungarian,

researcharxiv-cs-cl

Tutorials

MechSparse: Mechanism-Guided Sparse PEFT Selection Is Task-Shaped

arXiv:2609.18961v1 Announce Type: new Abstract: Mechanistic interpretability identifies sparse subsets of heads and MLP blocks that carry specific behaviors. We ask whether such causal signals can gui

tutorialsarxiv-cs-cl

Memory Has Geometry: Non-Uniform Geometric Memory for Long-Horizon Personalized AI

arXiv:2609.17969v1 Announce Type: new Abstract: Long-term memory is becoming a core substrate for personalized AI, yet most systems still represent personalization as discrete records in a largely sta

researcharxiv-cs-ai

Modelling Adjectival Modification Effects on Semantic Plausibility

arXiv:2507.21828v2 Announce Type: replace Abstract: While the task of assessing the plausibility of events such as 'news is relevant' has been addressed by a growing body of work, less attention has b

On-the-Fly Homographies Calibration for Multi-Camera Tracking

arXiv:2609.18582v1 Announce Type: cross Abstract: Precise multi-camera tracking traditionally relies on rigorous 3D site calibration, yet this requirement is often operationally impossible in large-sc

researcharxiv-cs-ai

Agents

One Axis, No Brake: Self-Knowledge Limits the Filtering of Harmful Peer Conformity in LLMs

arXiv:2609.18998v1 Announce Type: cross Abstract: Multi-agent LLM systems are expected to be more reliable because agents can catch each other's mistakes. But peer pressure cuts both ways: the same co

agentsarxiv-cs-cl

Patch the Distribution Mismatch: RL Rewriting Agent for Stable Off-Policy SFT

arXiv:2602.11220v2 Announce Type: replace-cross Abstract: Large language models are commonly adapted to downstream tasks through supervised fine-tuning (SFT), but substantial distribution mismatch bet

safetyarxiv-cs-cl

PersonaPath: Towards Knowledge-Centric Personalized Learning Path Planning

arXiv:2609.18861v1 Announce Type: new Abstract: Adaptive learning systems commonly formulate learning path planning as Exercise-Centric (EC) recommendation, where the next step is inferred from item-l

Playing log(N)-Questions over Wikipedia Abstracts: Communication Efficiency Between Paired Frontier Models

arXiv:2609.19113v1 Announce Type: new Abstract: We evaluate six frontier language models on the two-agent log(N)-Questions game. A questioner sees N Wikipedia lead paragraphs and must identify a secre

Procedural Pretraining for Molecular Property Prediction

arXiv:2609.17831v1 Announce Type: cross Abstract: Molecular property prediction is often limited by the small size of labeled downstream datasets, motivating pretraining on large corpora of unlabeled

SNOMED CT Concept Recommendation from Masked Clinical Context

arXiv:2609.17855v1 Announce Type: new Abstract: Standardizing clinical language to SNOMED CT supports interoperability, analytics, and reusable phenotyping, but concept recommendation remains difficul

Structured Claim-Level Discourse Representations for Dense Health Narratives

arXiv:2609.18905v1 Announce Type: new Abstract: Health discourse in social media videos often contains densely entangled claims spanning multiple thematic aspects, stances, evidential frames, and rhet

Symbolic Temporal Supervision of LLM Agents Using Contracts

arXiv:2609.18128v1 Announce Type: new Abstract: Large language model (LLM) agents augmented by tools can automate complex, multi-step tasks, such as web navigation, code generation, and workflow orche

safetyarxiv-cs-ai

Tutorials

TERN: A Delta-rule Memory with a Seasonal Reference and Online Adaptation for Epidemic Forecasting

arXiv:2609.18407v1 Announce Type: cross Abstract: Weekly influenza surveillance counts guide vaccine distribution and public-health alerts, yet they are hard to forecast. Each region offers only a few

tutorialsarxiv-cs-ai

Think Before You Comfort: Reflective Cognitive Alignment for Protocol-Grounded Elderly Stimulation Agents

arXiv:2609.17536v1 Announce Type: new Abstract: Cognitive Stimulation Therapy (CST) offers non-pharmacological support for elders with cognitive impairment, yet scalability remains constrained by reli

safetyarxiv-cs-cl

Today, we’re announcing Ternary Bonsai 2 27B. Based on Qwen3.8 27B, Bonsai 2 27B is 9x smaller than its full-precision counterpart while ret…

model-releasesemad-mostaque--x

Today, we’re announcing Ternary Bonsai 2 27B. Based on Qwen3.8 27B, Bonsai 2 27B is 9x smaller than its full-precision counterpart while retaining 98.2% of its aggregate benchmark performance. Two mon

Too Good to Be Real? Diagnosing and Reducing the Gap Between AI Preference and Real User Engagement

arXiv:2609.18282v1 Announce Type: new Abstract: Large language models are increasingly used to generate and evaluate online content, yet it remains unclear whether the qualities they associate with hi

researcharxiv-cs-cl

Tracing individual knowledge trajectories in a changing field: the case of general relativity and gravitation

arXiv:2609.18697v1 Announce Type: new Abstract: Historians have reconstructed the twentieth-century transformation of general relativity and gravitation (GRG) at the field level and through individual

safetyarxiv-cs-cl

Understanding Dynamic Scenes at Gigapixel Scale: Wide-Area Spatio-Temporal Perception from UAVs

arXiv:2609.18210v1 Announce Type: new Abstract: UAV-borne imaging has advanced from megapixel to gigapixel sensors, shifting aerial perception from recognizing individual targets to understanding enti

researcharxiv-cs-cv

Union stealth?

model-releasesr-localllama

Anyone else trying out the new Union stealth model on openrouter? It’s pretty good for a free model, and of course I had to run tokenizer tests and training cutoff tests which established it’s the 99%

WaveTLM: Reliable Time-Series Language Modeling through Task Compilation

model-releasesarxiv-cs-lg

arXiv:2609.18812v1 Announce Type: new Abstract: Time-series language models provide a shared natural-language interface across temporal tasks, but plausible text does not guarantee reliable task outpu

What makes Claude Projects so interesting is that it handles teams of agents really well, you talk to a main orchestrator agent and it spins…

model-releasesboris-cherny--x

What makes Claude Projects so interesting is that it handles teams of agents really well, you talk to a main orchestrator agent and it spins up specialists. Basically it creates an organization to sol

When Cognitive Graphs Meet LLMs: BDEI Cognitive Pathways for Panic Emotional Arousal Prediction

arXiv:2606.15121v3 Announce Type: replace Abstract: Predicting the timing of individual and collective panic emotional arousal before manifestation is essential for timely emergency intervention. Exis

Tutorials

When the Gradient Sees Rank: Provable Necessity, Causal Recruitment, and Composition in Trained Matrix Memories

arXiv:2609.17594v1 Announce Type: new Abstract: Can gradient-based training learn the rank needed to store and compose associations in a matrix memory? In our earlier study, we used a matrix-augmented

tutorialsarxiv-cs-lg

Where Should Agents Live? Energy-Memory Characterization of Agentic AI for the Edge-Cloud Continuum

arXiv:2609.18283v1 Announce Type: new Abstract: As telecommunication networks evolve toward autonomous 5G-Advanced and 6G operations, agentic artificial intelligence (AI) workflows, where large langua