Search: “llm”

Introducing Muse Code and Muse Spark 1.2

model-releasessimon-willison

Introducing Muse Code and Muse Spark 1.2 Yet more evidence that the most important characteristic of any model these days is long-sequence agentic tool calling. Meta shipped their own coding agent as

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IR2Solve: Structured Intermediate Representations for Cost-Efficient Optimization Autoformulation

DGX agent

arXiv:2608.02641v1 Announce Type: cross Abstract: Large language models (LLMs) can translate natural-language optimization problems into solver-ready formulations, but direct code generation is brittl

agentsarxiv-cs-ai

5 Aug 2026

Applications

Large language models for partial differential equation workflows

arXiv:2608.03600v1 Announce Type: new Abstract: Partial differential equations (PDEs) become actionable in science and engineering not as isolated formulae, but as executable workflows that connect mo

applicationsarxiv-cs-ai

Local Ai

Large Language Models provide support for the parallelogram theory of analogy

arXiv:2603.19066v2 Announce Type: replace-cross Abstract: Four-term word analogies (A:B::C:D) are classically modeled geometrically as parallelograms: adding the vector B-A+C produces D. Recent work s

local-aiarxiv-cs-ai

Utilize a nvidia gpu and amd gpu together for 2 different ai models?

model-releasesr-localllama

We run a local model instance in our company that the dev we hired built for us. We're a trade business and we want to further use our on hand hardware for it. The specs given we have is a 5090 gpu wi

Abstention as an Action Can Kill Both the Reward Gradient and the KL Anchor: Collapse Law and Repair for Error-Penalized Reinforcement Learning

arXiv:2608.00301v1 Announce Type: cross Abstract: Error-penalized scoring rules (+1 for a correct answer, -lambda for a wrong one, 0 for abstaining) are increasingly prescribed against hallucination:

agentsarxiv-cs-cl

Hardware

As AI Increases Demands on Memory, Storage Steps Up

Surging AI demands are driving the need for massive datasets and context windows that burst past the confines of system memory. But rising needs aren’t met by simply adding more storage capacity. What

hardwarenvidia-blog

AttnLink: Turning Attention into Schema Links for Text-to-SQL

arXiv:2608.00693v1 Announce Type: new Abstract: Schema linking is a critical component of Text-to-SQL systems, but existing approaches often trade off contextual modeling capacity, score-based control

Automatic Annotation of Ancient Greek Vowel Length

arXiv:2608.01935v1 Announce Type: new Abstract: Prior work in Ancient Greek NLP relies on corpora that do not disambiguate the phonemic vowel length of alpha, iota, and ypsilon, together known as the

BiCAA: Bidirectional Credit Assignment for Search-Augmented Agent

arXiv:2608.01321v1 Announce Type: new Abstract: Multi-step search is a fundamental capability for search agents, enabling them to iteratively acquire, refine, and integrate external evidence for compl

Bridging the English-Arabic Medical Knowledge Gap: Targeted Low-Rank Adaptation via Causal Layer Selection

arXiv:2608.00207v1 Announce Type: new Abstract: Large Language Models (LLMs) perform strongly in English medical tasks but degrade substantially in Arabic, a gap widely attributed to limited training

Comparing and Modeling Argumentation in German Political Communication across Arenas

arXiv:2608.00288v1 Announce Type: new Abstract: Deliberation, involving the formulation and exchange of arguments, forms an integral part of political decision making in democracies. Argumentation pat

Control Under Compression: Reliability Frontiers for Tool-Using Agents

arXiv:2608.01056v1 Announce Type: cross Abstract: Tool-using language-model agents are governed not only by task prompts but also by persistent system-side instructions that specify tools, arguments,

CRISP: Critical Step Perception for Training Efficient Deep Search Agents

arXiv:2608.01867v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly extended into deep search agents that solve complex questions through multi-step interaction with external

Fast and Accurate Quotation Attribution in Literary Texts

arXiv:2608.02359v1 Announce Type: new Abstract: Attributing quotations to their speakers in literary texts remains an open challenge. Standard methods, which independently predict a speaker mention fo

From We to Me: Theory Informed Narrative Shift with Abductive Reasoning

arXiv:2603.03320v2 Announce Type: replace Abstract: Effective communication often relies on aligning a message with an audience's narrative and worldview. Narrative shift involves transforming text to

Hierarchical Pre-Training of Vision Encoders with Large Language Model

arXiv:2604.00086v2 Announce Type: replace-cross Abstract: The field of computer vision has experienced significant advancements through scalable vision encoders and multimodal pre-training frameworks.

Tutorials

How to debug production AI agents with Signal in Arize AX

Learn how Arize Signal turns production traces into ranked issues, proposed fixes, regression datasets, and reviewable pull requests for AI agents. The post How to debug production AI agents with Sign

tutorialsarize-ai

Interpretable Recognition of Cognitive Distortions in Natural Language Texts

arXiv:2511.05969v2 Announce Type: replace Abstract: We propose a new approach to multi-factor classification of natural language texts based on weighted structured patterns such as N-grams, taking int

LangFIR: Discovering Sparse Language-Specific Features from Monolingual Data for Language Steering

arXiv:2604.03532v2 Announce Type: replace Abstract: Large language models (LLMs) show strong multilingual capabilities, yet reliably controlling the language of their outputs remains difficult. Repres

Leak It: A Probabilistic Approach to Training-Data Extraction from Black-Box Language Models

arXiv:2608.00144v1 Announce Type: cross Abstract: Membership inference (MIA) on language models is usually summarised by an aggregate ROC-AUC, but such evaluations are confounded: model-free blind bas

OpenART: Scaling Agent Red Teaming via Open-Ended Environment Evolution

arXiv:2608.00677v1 Announce Type: new Abstract: AI agents operate in persistent environments where early state changes can influence decisions far into the future. Unlike conventional language-model i

PredAct-Bench: Benchmarking Tool-Augmented Dialogue under Controlled Tool Noise

arXiv:2608.02372v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in task-oriented dialogue systems that support multi-step decision-making in high-stakes domains

Pruned BPE: Post-training Visibility Pruning and Token Reallocation for Byte Pair Encoding

arXiv:2608.00837v1 Announce Type: new Abstract: Byte Pair Encoding (BPE) is widely used for subword tokenization, but standard BPE exposes every learned merge token to the downstream model, including

QR-Erase: Efficient Subspace-Based Machine Unlearning with Layer Localization

arXiv:2608.01422v1 Announce Type: new Abstract: Machine unlearning seeks to remove targeted information from trained models without requiring costly retraining. Existing optimization-based methods oft

Qwen-CUA: Native Computer Use for (almost) Everything

arXiv:2608.02352v1 Announce Type: cross Abstract: Native computer use offers a general interface for agents to operate almost any software available to people, but requires long-horizon state tracking

Role Steering of Language Models for Social Simulations

arXiv:2608.00023v1 Announce Type: new Abstract: Social simulations built from language-model agents need role-conditioned behavior that can be checked before agents are placed into a simulated populat

Semantic Alignment of AI Models: Concept Collapse, Checkpoint Dynamics, and Cross-Lingual Transfer

arXiv:2608.01585v1 Announce Type: new Abstract: Language model benchmarking is a difficult task. Outcome reasoning alone does not test the model's conceptualization of language and popular open-source

SERL-SQL: Selective Hindsight Distillation for Text-to-SQL Reinforcement Agentic Learning

arXiv:2608.00485v1 Announce Type: new Abstract: Recent Text-to-SQL systems increasingly rely on multi-turn interaction, execution feedback, and reinforcement learning. However, most existing methods u

Sixteen models, fewer than two voices: measuring ensemble dispersion where no answer is uniquely correct

arXiv:2608.00285v1 Announce Type: new Abstract: Sixteen language models drawn from ten families produced, on average, the semantic diversity of 1.69 distinct formulations of a psychotherapeutic case,

TAB-PO: Preference Optimization with a Token-Level Adaptive Barrier for Token-Critical Structured Generation

arXiv:2603.00025v3 Announce Type: replace Abstract: Direct Preference Optimization (DPO) is effective for offline alignment but poorly matched to ontology-driven structured prediction, where preferred

The Learning Objective Governs Perceptual Narrowing: A Cross-Lingual, Layer-Wise, Ten-Seed Study of Self-Supervised Speech Encoders

arXiv:2608.00507v1 Announce Type: new Abstract: Perceptual narrowing---the developmental loss of non-native phoneme discrimination in the first year of life itep{werker1984}---is a canonical developme

Understanding Sparse Attention Selectivity in Long-Context Foundation Models via Counterfactual Evaluation

arXiv:2608.01676v1 Announce Type: new Abstract: Sparse attention is widely deployed in long-context serving stacks, yet no framework audits how discarding blocks changes the influence of specific cont

Advanced reasoning and problem-solving, plus strong performance in Japanese language and Japan-specific context. Namazu is live on Merge Gat…

Advanced reasoning and problem-solving, plus strong performance in Japanese language and Japan-specific context. Namazu is live on Merge Gateway now! https://x.com/SakanaAILabs/status/2084276852143919

researchdavid-ha--x

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives

arXiv:2607.29064v1 Announce Type: cross Abstract: Police crash narratives contain information that may supplement structured crash databases, but manual review is labor-intensive and it remains unclea

Can AI Evaluate AI Scientists? A Benchmarking Study of Autonomous Research Generation Systems Using Automated Multi-Model Review

arXiv:2607.28631v1 Announce Type: new Abstract: AI Scientist systems capable of autonomous research have the potential to significantly accelerate scientific discovery. However, evaluating and compari

Don't Mix Rewards, Mix Policies: Policy Decomposition and Optimization for Multi-Reward RL

arXiv:2607.29246v1 Announce Type: new Abstract: Modern large language models (LLMs) are expected not just to answer correctly, but to adapt their behavior to different human values and use cases. As a

safetyarxiv-cs-ai

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat

arXiv:2607.29577v1 Announce Type: new Abstract: Games and simulators make valuable benchmarks by turning decisions into measurable outcomes, but many current suites under-test rules-rich tactical reas

EarlyDx: An Admission-Anchored Benchmark for Open-Ended Generation of Evidence-Supported ED-Encounter Diagnoses

arXiv:2607.28788v1 Announce Type: new Abstract: Clinical diagnosis at hospital admission must be made rapidly from limited, incomplete evidence. Existing diagnosis-prediction benchmarks are poorly sui

ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics

arXiv:2603.11872v3 Announce Type: replace-cross Abstract: Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI sy

agentsarxiv-cs-ai

Estimating near-verbatim extraction risk in language models with decoding-constrained beam search

arXiv:2603.24917v3 Announce Type: replace Abstract: Recent work shows that standard greedy-decoding extraction methods for quantifying memorization in LLMs miss how extraction risk varies across seque

FineInstructions: Scaling Synthetic Instructions to Pre-Training Scale

arXiv:2601.22146v3 Announce Type: replace Abstract: Due to limited supervised training data, large language models (LLMs) are typically pre-trained via a self-supervised 'predict the next word' object

Generative AI in Action: Field Experimental Evidence from Alibaba's Customer Service Operations

arXiv:2603.29888v2 Announce Type: replace-cross Abstract: In collaboration with Alibaba, we study how a generative AI assistant affects service performance in e-commerce after-sales operations. In a l

agentsarxiv-cs-ai

HAM-VLN: Harnessing Hierarchical Agentic Memory for Zero-Shot Vision-and-Language Navigation

arXiv:2607.29600v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) enables robots to follow instructions in previously unseen environments. Recently, a training-free paradigm has eme

agentsarxiv-cs-ro

Language Models Agree With Each Other, Not With Readers

arXiv:2607.29274v1 Announce Type: cross Abstract: Claims that language models homogenise are usually measured against human judgements collected for the study, which makes the human side an artifact o

Learning Latent Reasoning Traces for Scalar Reward Models End-to-End

arXiv:2607.29185v1 Announce Type: new Abstract: Reward models (RMs) are central to aligning large language models with human preferences via reinforcement learning. Although traditional scalar RMs ena

Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent Failures

arXiv:2607.28802v1 Announce Type: new Abstract: Existing evaluations often reduce agent failures to system-level outcomes, obscuring where the fault originated and which intervention would improve the

MPP-GNN: Subject-Adaptive Community Detection for fMRI-Based Alzheimer's Disease Classification

arXiv:2607.28681v1 Announce Type: cross Abstract: Functional magnetic resonance imaging (fMRI) is a widely used technique for studying the brain. Recent methods that utilize graph neural networks (GNN

safetyarxiv-cs-ai