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Abhinav Kumar

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Preprint Oct 2026

SCARCE: Emergent Institutions in Long-Horizon Multi-Agent Coding Systems

As autonomous agents become widely deployed, coordinating access to shared computing resources and services will become increasingly important. Recent incidents have already revealed unplanned coordination between agents, highlighting the safety implications of these interactions. Yet prior studies of agent negotiation...

Abhinav Kumar, Rediet Abebe, E. Bagdasarian et al. · 0 citations
#artificial intelligence Preprint Oct 2026

SCARCE: Emergent Institutions in Long-Horizon Multi-Agent Coding Systems

As autonomous agents become widely deployed, coordinating access to shared computing resources and services will become increasingly important. Recent incidents have already revealed unplanned coordination between agents, highlighting the safety implications of these interactions. Yet prior studies of agent negotiation...

Abhinav Kumar, Rediet Abebe, E. Bagdasarian et al. · 0 citations
#natural language process... Preprint Sep 2026

Authority Bias in Language Models: Source Deference and User Agreement Are Not Interchangeable

Language models tend to agree with whatever a user asserts, and post-training increasingly targets this sycophancy so that models evaluate claims on their merits rather than deferring to the user. Yet the same models are far more compliant when a wrong answer is attributed to a verified source, which is how retrieval r...

Abhinav Kumar, Paras Chopra · 2 citations

OverThink: Slowdown Attacks on Reasoning LLMs

This work evaluates Overthink on proprietary and open-source reasoning models across the FreshQA, SQuAD, and MuSR datasets, and shows that newer generations of RLMs, while showing a drastic increase in per-token cost, also exhibit up to a 2.3x increase in reasoning tokens, leaving them more vulnerable to Overthink atta...

Abhinav Kumar, Jaechul Roh, Ali Naseh et al. · 92 citations · ⚡9
#machine learning Preprint Sep 2026

DeFiFlowBench: Benchmarking and Improving Safe Executability in Natural-Language DeFi Workflow Synthesis

The proposed Koan-Safe, which combines a prompt-only intent parser, a replaceable generator, and structural repair with default safety parameters, is proposed, which supports explicit trade protections and execution-based evaluation, while distinguishing declared safety from a general guarantee.

Abhinav Kumar, Harshit Arora, Varun Singh et al. · 0 citations
Preprint Jul 2026

PiSAs: Benchmarking Contextual Integrity in Multi-User Agentic Systems

PiSAs (Privacy in Shared Agentic systems), a benchmark for assessing unintentional leaks with dual CI annotations, enables direct measurement of cross-user spillage across agentic system components and interfaces, such as outputs, inter-agent communication, and memory.

Shubham Gupta, N. Sepahvand, Abhinav Kumar et al. · 0 citations

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