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researcher

Volker Tresp

24 papers hereh-index 10397 citations31 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author10
  • last author9

Across the 20 of 24 papers where every author was matched, so the position is known.

fields
  • cs.CV10
  • cs.LG5
  • cs.AI4
  • cs.CL3
  • cs.CR2
same name
  • Volker Tresp — 54 papers, h 32
  • Volker Tresp — 35 papers, h 59
  • Volker Tresp — 14 papers, h 3
  • Volker Tresp — 14 papers, h 2
  • Volker Tresp — 9 papers
  • Volker Tresp — 2 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedVideoINSTA: Zero-shot Long Video Understanding via Informative Spatial-Temporal Reasoning with LLMs

1 citations · 2 across the 15 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

QuoteBench: How Matched Scores Can Hide Command-Path Failures

Shangao Li, Yao Zhang, Volker Tresp +1

LLM coding agents issue Bash commands through interfaces that may serialize, wrap, and reparse model output. Matched execution scores alone cannot distinguish command-generation er…

cs.AI2026

WebArbiter: A Principle-Guided Reasoning Process Reward Model for Web Agents

Yao Zhang, Shijie Tang, Zeyu Li +2

Web agents hold great potential for automating complex computer tasks, yet their interactions involve long-horizon, sequential decision-making with irreversible actions. In such se…

cs.AI2025

GroundedPRM: Tree-Guided and Fidelity-Aware Process Reward Modeling for Step-Level Reasoning

Yao Zhang, Yu Wu, Haowei Zhang +6

Process Reward Models (PRMs) aim to improve multi-step reasoning in Large Language Models (LLMs) by supervising intermediate steps and identifying errors. However, building effecti…

cs.AI2024

How the (Tensor-) Brain uses Embeddings and Embodiment to Encode Senses and Symbols

Volker Tresp, Hang Li

The Tensor Brain (TB) has been introduced as a computational model for perception and memory. This paper provides an overview of the TB model, incorporating recent developments and…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.