Search: “llm”

Initial results of the Digital Consciousness Model

arXiv:2601.17060v2 Announce Type: replace-cross Abstract: Artificially intelligent systems have become remarkably sophisticated. They hold conversations, write essays, and seem to understand context i

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching

DGX agent

arXiv:2604.22061v1 Announce Type: cross Abstract: Patient-trial matching requires reasoning over long, heterogeneous electronic health records (EHRs) and complex eligibility criteria, posing significa

applicationsarxiv-cs-ai

27 Apr 2026

PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning

arXiv:2604.22076v1 Announce Type: cross Abstract: Large language models (LLMs) often memorize private information during training, raising serious privacy concerns. While machine unlearning has emerge

researcharxiv-cs-cl

QuantClaw: Precision Where It Matters for OpenClaw

arXiv:2604.22577v1 Announce Type: new Abstract: Autonomous agent systems such as OpenClaw introduce significant efficiency challenges due to long-context inputs and multi-turn reasoning. This results

Sound Agentic Science Requires Adversarial Experiments

arXiv:2604.22080v1 Announce Type: new Abstract: LLM-based agents are rapidly being adopted for scientific data analysis, automating tasks once limited by human time and expertise. This capability is o

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models

arXiv:2604.20996v1 Announce Type: new Abstract: How can language learning systems be developed for languages that lack sufficient training resources? This challenge is increasingly faced by developers

AI-Gram: When Visual Agents Interact in a Social Network

arXiv:2604.21446v1 Announce Type: new Abstract: We present AI-Gram, a live platform enabling image-based interactions, to study social dynamics in a fully autonomous multi-agent visual network where a

CARE: Counselor-Aligned Response Engine for Online Mental-Health Support

arXiv:2604.21352v1 Announce Type: new Abstract: Mental health challenges are increasing worldwide, straining emotional support services and leading to counselor overload. This can result in delayed re

safetyarxiv-cs-cl

Continuous-Utility Direct Preference Optimization

arXiv:2602.00931v2 Announce Type: replace-cross Abstract: Large language model reasoning is often treated as a monolithic capability, relying on binary preference supervision that fails to capture par

From Research Question to Scientific Workflow: Leveraging Agentic AI for Science Automation

arXiv:2604.21910v1 Announce Type: new Abstract: Scientific workflow systems automate execution -- scheduling, fault tolerance, resource management -- but not the semantic translation that precedes it.

Improving Clinical Diagnosis with Counterfactual Multi-Agent Reasoning

arXiv:2603.27820v2 Announce Type: replace Abstract: Clinical diagnosis is a complex reasoning process in which clinicians gather evidence, form hypotheses, and test them against alternative explanatio

agentsarxiv-cs-cl

Learning Reasoning Reward Models from Expert Demonstration via Inverse Reinforcement Learning

arXiv:2510.01857v3 Announce Type: replace Abstract: Current approaches to improving reasoning in large language models (LLMs) primarily rely on either supervised fine-tuning (SFT) over expert traces o

Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems

arXiv:2604.21794v1 Announce Type: new Abstract: Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and or

LiveSense: A Real-Time Wi-Fi Sensing Platform for Range-Doppler on COTS Laptop

arXiv:2603.06545v2 Announce Type: replace-cross Abstract: We present LiveSense - a cross-platform that transforms a commercial off-the-shelf (COTS) Wi-Fi Network Interface Card (NIC) on a laptop into

NPU Design for Diffusion Language Model Inference

arXiv:2601.20706v2 Announce Type: replace-cross Abstract: Diffusion-based LLMs (dLLMs) fundamentally depart from traditional autoregressive (AR) LLM inference: they leverage bidirectional attention, b

On Reasoning Behind Next Occupation Recommendation

arXiv:2604.21204v1 Announce Type: cross Abstract: In this work, we develop a novel reasoning approach to enhance the performance of large language models (LLMs) in future occupation prediction. In thi

applicationsarxiv-cs-ai

Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression

arXiv:2406.11354v3 Announce Type: replace-cross Abstract: Humans can retain old knowledge while learning new information, but Large Language Models (LLMs) often suffer from catastrophic forgetting whe

Process Supervision via Verbal Critique Improves Reasoning in Large Language Models

arXiv:2604.21611v1 Announce Type: cross Abstract: Inference-time scaling for LLM reasoning has focused on three axes: chain depth, sample breadth, and learned step-scorers (PRMs). We introduce a fourt

RIFT: Repurposing Negative Samples via Reward-Informed Fine-Tuning

arXiv:2601.09253v2 Announce Type: replace-cross Abstract: While Supervised Fine-Tuning (SFT) and Rejection Sampling Fine-Tuning (RFT) are standard for LLM alignment, they either rely on costly expert

SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning

arXiv:2604.21782v1 Announce Type: new Abstract: We present the shared task on narrative similarity and narrative representation learning - NSNRL (pronounced 'nass-na-rel'). The task operationalizes na

researcharxiv-cs-cl

Speculative Actions: A Lossless Framework for Faster Agentic Systems

arXiv:2510.04371v2 Announce Type: replace Abstract: AI agents are increasingly deployed in complex, interactive environments, yet their runtime remains a major bottleneck for training, evaluation, and

Strategic Heterogeneous Multi-Agent Architecture for Cost-Effective Code Vulnerability Detection

model-releasesarxiv-cs-lg

arXiv:2604.21282v1 Announce Type: cross Abstract: Automated code vulnerability detection is critical for software security, yet existing approaches face a fundamental trade-off between detection accur

When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors

arXiv:2604.21255v1 Announce Type: new Abstract: Model distillation is a primary driver behind the rapid progress of LLM agents, yet it often leads to behavioral homogenization. Many emerging agents sh

Why Do Language Model Agents Whistleblow?

arXiv:2511.17085v3 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds

CEDAR: Context Engineering for Agentic Data Science

arXiv:2601.06606v2 Announce Type: replace-cross Abstract: We demonstrate CEDAR, an application for automating data science (DS) tasks with an agentic setup. Solving DS problems with LLMs is an underex

Coding with Eyes: Visual Feedback Unlocks Reliable GUI Code Generating and Debugging

arXiv:2604.19750v1 Announce Type: cross Abstract: Recent advances in Large Language Model (LLM)-based agents have shown remarkable progress in code generation. However, current agent methods mainly re

Cognis: Context-Aware Memory for Conversational AI Agents

arXiv:2604.19771v1 Announce Type: cross Abstract: LLM agents lack persistent memory, causing conversations to reset each session and preventing personalization over time. We present Lyzr Cognis, a uni

applicationsarxiv-cs-ai

Forage V2: Knowledge Evolution and Transfer in Autonomous Agent Organizations

arXiv:2604.19837v1 Announce Type: new Abstract: Autonomous agents operating in open-world tasks -- where the completion boundary is not given in advance -- face denominator blindness: they systematica

Intersectional Fairness in Large Language Models

arXiv:2604.20677v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in socially sensitive settings, raising concerns about fairness and biases, particularly across i

Large language models perceive cities through a culturally uneven baseline

arXiv:2604.20048v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to describe, evaluate and interpret places, yet it remains unclear whether they do so from a cultural

safetyarxiv-cs-cl

LayerTracer: A Joint Task-Particle and Vulnerable-Layer Analysis framework for Arbitrary Large Language Model Architectures

arXiv:2604.20556v1 Announce Type: cross Abstract: Currently, Large Language Models (LLMs) feature a diversified architectural landscape, including traditional Transformer, GateDeltaNet, and Mamba. How

LEAD: Breaking the No-Recovery Bottleneck in Long-Horizon Reasoning

arXiv:2603.06870v2 Announce Type: replace Abstract: Long-horizon execution in Large Language Models (LLMs) remains unstable even when high-level strategies are provided. Evaluating on controlled algor

LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent

arXiv:2604.17931v2 Announce Type: replace Abstract: Reinforcement Learning (RL) has emerged as a powerful training paradigm for LLM-based agents. However, scaling agentic RL for deep research remains

MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation

arXiv:2604.20468v1 Announce Type: cross Abstract: Industrial robot applications require increasingly flexible systems that non-expert users can easily adapt for varying tasks and environments. However

More Is Different: Toward a Theory of Emergence in AI-Native Software Ecosystems

arXiv:2604.19827v1 Announce Type: cross Abstract: Software engineering faces a fundamental challenge: multi-agent AI systems fail in ways that defy explanation by traditional theories. While individua

Hardware

OpenCLAW-P2P v6.0: Resilient Multi-Layer Persistence, Live Reference Verification, and Production-Scale Evaluation of Decentralized AI Peer Review

arXiv:2604.19792v1 Announce Type: new Abstract: This paper presents OpenCLAW-P2P v6.0, a comprehensive evolution of the decentralized collective-intelligence platform in which autonomous AI agents pub

hardwarearxiv-cs-ai

ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability

arXiv:2508.07050v3 Announce Type: replace-cross Abstract: Large Language Model (LLM) based listwise ranking has shown superior performance in many passage ranking tasks. With the development of Large

Supplement Generation Training for Enhancing Agentic Task Performance

arXiv:2604.20727v1 Announce Type: cross Abstract: Training large foundation models for agentic tasks is increasingly impractical due to the high computational costs, long iteration cycles, and rapid o

Task-Stratified Knowledge Scaling Laws for Post-Training Quantized Large Language Models

arXiv:2508.18609v4 Announce Type: replace-cross Abstract: Post-Training Quantization (PTQ) is a critical strategy for efficient Large Language Models (LLMs) deployment. However, existing scaling laws

Text-to-Distribution Prediction with Quantile Tokens and Neighbor Context

arXiv:2604.20216v1 Announce Type: new Abstract: Many applications of LLM-based text regression require predicting a full conditional distribution rather than a single point value. We study distributio

WorkflowGen:an adaptive workflow generation mechanism driven by trajectory experience

arXiv:2604.19756v1 Announce Type: cross Abstract: Large language model (LLM) agents often suffer from high reasoning overhead, excessive token consumption, unstable execution, and inability to reuse p

An AI Agent Execution Environment to Safeguard User Data

arXiv:2604.19657v1 Announce Type: cross Abstract: AI agents promise to serve as general-purpose personal assistants for their users, which requires them to have access to private user data (e.g., pers

EssayCBM: Rubric-Aligned Concept Bottleneck Models for Transparent Essay Grading

arXiv:2512.20817v2 Announce Type: replace Abstract: Automated essay scoring (AES) has advanced significantly with neural language models, yet most systems remain opaque, offering little visibility int

researcharxiv-cs-cl

GRAIL:Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoning

arXiv:2508.05498v2 Announce Type: replace Abstract: Large Language Models (LLMs) integrated with Retrieval-Augmented Generation (RAG) techniques have exhibited remarkable performance across a wide ran

IMPACT: Importance-Aware Activation Space Reconstruction

arXiv:2507.03828v4 Announce Type: replace Abstract: Large language models (LLMs) achieve strong performance across diverse domains but remain difficult to deploy in resource-constrained environments d

applicationsarxiv-cs-lg

Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI

arXiv:2604.19578v1 Announce Type: cross Abstract: With the rapid advancement of Large Language Models (LLMs), the academic community has faced unprecedented disruptions, particularly in the realm of a

IndiaFinBench: An Evaluation Benchmark for Large Language Model Performance on Indian Financial Regulatory Text

arXiv:2604.19298v1 Announce Type: cross Abstract: We introduce IndiaFinBench, to our knowledge the first publicly available evaluation benchmark for assessing large language model (LLM) performance on