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30 results for "llm"

SEEKING ALPHA

Hillman Solutions Corp. 2026 Q1 - Results - Earnings Call Presentation

2026-04-28. The following slide deck was published by Hillman Solutions Corp.…

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ARXIV.ORG

LLMs Corrupt Your Documents When You Delegate

Large Language Models (LLMs) are poised to disrupt knowledge work, with the emergence of delegated work as a new interaction paradigm (e.g., vibe coding). Delegation requires trust - the expectation t…

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GITHUB

Sage-Wiki: An LLM-compiled personal knowledge base

An LLM-compiled personal knowledge base. Drop in your papers, articles, and notes. sage-wiki compiles them into a structured, interlinked wiki — with concepts extracted, cross-references discovere...…

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NEWSWEEK

Yann LeCun: LLMs Are Nearing the End, but Better AI Is Coming (2025)

Yann LeCun, Chief AI Scientist at Meta, believes LLMs are doomed due to their inability to represent the high-dimensional spaces that characterize our world…

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DEV COMMUNITY

We Fixed Karpathy’s LLM Wiki - PENgram Is the Typed Knowledge Graph Pipeline Everyone Asked For

We recently published an article about the gaps in Karpathy's LLM Wiki pattern. The thesis was...…

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GITHUB

Show HN: Waiting for LLMs Suck – Give your user a game

Give your user a game while they wait for the LLM to return a result.…

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ARXIV.ORG

Don't Make the LLM Read the Graph: Make the Graph Think

We investigate whether explicit belief graphs improve LLM performance in cooperative multi-agent reasoning. Through 3,000+ controlled trials across four LLM families in the cooperative card game Hanab…

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ARXIV.ORG

Analytica: Soft Propositional Reasoning for Robust and Scalable LLM-Driven Analysis

Large language model (LLM) agents are increasingly tasked with complex real-world analysis (e.g., in financial forecasting, scientific discovery), yet their reasoning suffers from stochastic instabili…

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ARXIV.ORG

Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach

Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language models (LLMs) show promise, it remains unclear …

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ARXIV.ORG

PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks

The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In such an attack, a malicious actor uses Augmented R…

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ARXIV.ORG

Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines

LLM-as-a-Judge has become the dominant paradigm for evaluating language model outputs, yet LLM judges exhibit systematic biases that compromise evaluation reliability. We present a comprehensive empir…

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ARXIV.ORG

CAP-CoT: Cycle Adversarial Prompt for Improving Chain of Thoughts in LLM Reasoning

Chain-of-Thought (CoT) prompting has emerged as a simple and effective way to elicit step-by-step solutions from large language models (LLMs). However, CoT reasoning can be unstable across runs on lon…

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ARXIV.ORG

LEGO: An LLM Skill-Based Front-End Design Generation Platform

Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design and debugging strategies. We present LEGO, a un…

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ARXIV.ORG

GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs

Autonomous multi-agent LLM systems are increasingly deployed to investigate operational incidents and produce structured diagnostic reports. Their trustworthiness hinges on whether each claim is groun…

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ARXIV.ORG

Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task

Large language models (LLMs) have shown strong performance on legal benchmarks, including multiple-choice components of bar exams. However, their capacity for generating open-ended legal reasoning in …

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ARXIV.ORG

ClawTrace: Cost-Aware Tracing for LLM Agent Skill Distillation

Skill-distillation pipelines learn reusable rules from LLM agent trajectories, but they lack a key signal: how much each step costs. Without per-step cost, a pipeline cannot distinguish adding a missi…

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ARXIV.ORG

LLM-Augmented Traffic Signal Control with LSTM-Based Traffic State Prediction and Safety-Constrained Decision Support

Traffic signal control is a critical task in intelligent transportation systems, yet conventional fixed-time and rule-based methods often struggle to adapt to dynamic traffic demand and provide limite…

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ARXIV.ORG

Context-Aware Hospitalization Forecasting Evaluations for Decision Support using LLMs

Medical and public health experts must make real-time resource decisions, such as expanding hospital bed capacity, based on projected hospitalization trends during large-scale healthcare disruptions (…

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ARXIV.ORG

LLM-Guided Agentic Floor Plan Parsing for Accessible Indoor Navigation of Blind and Low-Vision People

Indoor navigation remains a critical accessibility challenge for the blind and low-vision (BLV) individuals, as existing solutions rely on costly per-building infrastructure. We present an agentic fra…

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ARXIV.ORG

Multi-Dimensional Evaluation of Sustainable City Trips with LLM-as-a-Judge and Human-in-the-Loop

Evaluating nuanced conversational travel recommendations is challenging when human annotations are costly and standard metrics ignore stakeholder-centric goals. We study LLMs-as-Judges for sustainable…

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ARXIV.ORG

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator

The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific evaluation datasets; however, the collection of such…

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ARXIV.ORG

The Price of Agreement: Measuring LLM Sycophancy in Agentic Financial Applications

Given the increased use of LLMs in financial systems today, it becomes important to evaluate the safety and robustness of such systems. One failure mode that LLMs frequently display in general domain …

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PREPROMPT

PrePrompt – MCP server that rewrites vague prompts before they reach the LLM

MCP server that intercepts and optimizes prompts in Claude Code and Cursor before they reach the LLM. Zero noise, sub-ms latency, runs locally.…

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SEEKING ALPHA

Hillman Solutions Corp. (HLMN) Q1 2026 Earnings Call Transcript

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GITHUB

PAVO-Bench – 50K voice turns and an 85K-param router for ASR→LLM→TTS

A 50K-turn voice pipeline benchmark and an 85K-param meta-controller that cuts P95 latency 10.3% and energy 71% vs fixed cloud. TMLR 2026. - vnmoorthy/pavo-bench…

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HACKER NEWS: SHOW HN

Show HN: VoiceGoat – A vulnerable voice agent for practicing LLM attacks

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MACHINE LEARNING

The loss curve said tie. The judges said otherwise. Seeking replication for an early LLM training result [R]

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ALL NEWS

Stride earnings up next: Can enrollment rebound from tech crisis?

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STABLEDIFFUSION

Built a Character Portrait Generator that reads books, identifies characters, and generates consistent portraits using ComfyUI (full RAG pipeline, local LLM, open-source)

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YAHOO FINANCE

Hillman Solutions Q1 Earnings Call Highlights

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