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Showing papers from George Washington University Show all papers

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NeurIPS 2026U CambridgePalisade ResearchKorea Advanced Institute of ScieMATSGeorge WashingtonAlignment & preference optimization

Symmetric Interventions for Eliciting Model Intent

David Vella Zarb, Rustem Turtayev, Taywon Min, Jinghua Ou and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026TsinghuaInstitute for AI Industry ResearInstitute of AI Industry ResearcU the Chinese Academy of ScienceDell TechnologyLLM evaluation & benchmarks

CSBench: A Comprehensive Benchmark for Evaluating Project-Level System Construction in Computer Science

Hongli Yu, Huan-ang Gao, Botian Wang, Hanlin Wu and 11 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026George WashingtonThe University of Texas at DallaRL for LLMs

OPPO: Bayesian Value Recursion for Token-Level Credit Assignment in Policy Optimization

Yu Li, Rui Miao, Tian Lan, Zhengling Qi

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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69%Highly rated
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NeurIPS 2026George WashingtonGoogleU California, BerkeleyAI oversight & deception

Self-Recognition Finetuning can Reverse and Prevent Emergent Misalignment

Arush Tagade, Shaoheng Zhou, Jiaxin Wen, Shi Feng

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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3/20 AI panelreviewers recommend it

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AI panel: 3 of 20 reviewers recommend it
lenient 1/5
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71%Highly rated
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NeurIPS 2026AIR, TsinghuaTsinghuaGeorge WashingtonPrivacy

Position: Life-Logging Video Streams Make the Privacy–Utility Trade-off Inevitable

Always-on life-logging video makes the privacy-utility trade-off inevitable for persistent AI, requiring pipeline-aware designs and formal leakage metrics.

Tianyuan Zou, Liang Yue, Yang Liu, Ya-Qin Zhang and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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7/20 AI panelreviewers recommend it

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AI panel: 7 of 20 reviewers recommend it
lenient 5/5
medium 2/10
strict 0/5
74%Highly rated
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NeurIPS 2026George WashingtonAlignment & preference optimization

INSPO : Unlocking Intrinsic Self-Reflection for LLM Preference Optimization

InSPO derives a globally optimal preference policy conditioning on alternative responses, proving superiority to DPO while guaranteeing invariance to modeling choices and improving alignment.

Yu Li, Tian Lan, Zhengling Qi

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 3/5
medium 6/10
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88%Must read
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NeurIPS 2026U California, IrvineThe University of Texas at DallaGeorge WashingtonU California, Santa BarbaraDeep RL

TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing

TOPPO balances critic gradients to fix PPO's multi-task ill-conditioning, outperforming SAC baselines with fewer parameters and steps.

Yuanpeng Li, Rui Miao, Gefei Lin, Annie Qu

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 2/5